Projects & Theses
Below you find a collection of BSc and MSc projects and theses that can be carried out within the MaP community.
Development of Wireless Ion Sensing Platforms using Metamaterials and Soft Biointerfaces
This project explores the design and realization of a flexible, wireless ion-sensing patch by integrating resonant metamaterial structures with bio-interfacing soft materials. The system is intended for noninvasive detection of physiologically relevant ions from skin-interfaced fluids using passive sensing mechanisms
Keywords
flexible electronics, metamaterials, wireless biosensors, resonant sensors, skin-compatible interfaces
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-23 , Earliest start: 2026-01-15 , Latest end: 2026-10-29
Organization Biomedical and Mobile Health Technology Lab
Hosts Zada Muhammad
Topics Engineering and Technology
Multi agent motion planning with (learned) behaviours
We want to incorporate learned skills and preprogrammed controllers into multi agent planning.
Keywords
multi agent motion planning
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Master Thesis
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Published since: 2025-12-22 , Earliest start: 2026-01-01
Organization Computational robotics laboratory (Prof. Stelian Coros)
Hosts Hartmann Valentin
Topics Information, Computing and Communication Sciences
Benchmarking robotic multi agent reinforcement learning
Good task allocation is crucial for efficiency in multi robot systems. We want to benchmark algorithms and approaches for this problem in this thesis.
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Semester Project , Master Thesis
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Published since: 2025-12-22
Organization Computational robotics laboratory (Prof. Stelian Coros)
Hosts Hartmann Valentin
Topics Information, Computing and Communication Sciences , Engineering and Technology
Learning precise cube reorientation from human priors
Dexterous multi finger tasks are still hard. We want to evaluate reinforcement learning with human priors for the cube reorientation task in this work.
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Master Thesis
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Published since: 2025-12-22
Organization Computational robotics laboratory (Prof. Stelian Coros)
Hosts Hartmann Valentin
Topics Information, Computing and Communication Sciences , Engineering and Technology
In vitro liver models for high-throughput screening of pro-regenerative treatments to recondition human organs for transplantation
Many organ grafts are not suitable for transplantation due to excessive ischemic injury. In an effort to save these discarded grafts, ex vivo perfusion systems have been developed to extend the time window for organ repair. The liver, in particular, has a remarkable regenerative capacity and its ex vivo perfusion provides a unique opportunity to trigger regeneration pathways. Thus far, advanced perfusion technologies have enabled the preservation of the human liver outside of the body for up to two weeks using normothermic machine perfusion. Until now, this liver perfusion machine has only been employed to treat bacterial infections, determine tumour malignancy and assess liver function, yet how to stimulate growth and repair of liver grafts ex vivo remains unexplored. In order to effectively develop regeneration strategies, in vitro liver models are necessary since ex vivo human liver experiments are low-throughput, confounded by patient to patient variability and costly. Liver tissue slices, which are directly obtained from native liver tissue, preserve the intact hepatocellular architecture and microenvironment of the liver unlike 2D cell culture and organoid models. Thus, we aim to use liver tissue slices as a screening platform to identify pro-regenerative biomolecules and drugs. In addition, we will explore mRNA lipid nanoparticles to improve the delivery and therapeutic effect of candidate biomolecules and drugs for ex vivo liver perfusion.
Keywords
in vitro liver models, regeneration, drug screening, cell culture, molecular biology, biomedical engineering, high-throughput, mRNA LNP, drug delivery systems, in vitro model, liver, translation
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Internship , Master Thesis
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Published since: 2025-12-21 , Earliest start: 2026-01-11 , Latest end: 2026-12-31
Organization Macromolecular Engineering Laboratory
Hosts Cunningham Leslie
Topics Engineering and Technology , Biology
Optical Glucose Sensor for a Perfusion System
Organ perfusion is a method by which blood and other fluids are oxygenated and pumped through organs including livers, kidneys, lungs and hearts in order to provide the organ with oxygen and nutrients. Various organ perfusion technologies are already in clinical use to improve organ preservation or even treat organs prior to transplantation. Furthermore, ex-vivo perfusion offers the unique opportunity to study whole organs as an isolated system. Robust organ perfusion systems require close control of perfusate parameters such as pH, oxygenation, flow, pressure, glucose concentration etc. While some parameters such as flow and pressure can be monitored with reusable sensors, others like pH, oxygenation and glucose require disposable sensors that are expensive and can only be used once. Because of high costs of these sensors, most perfusion systems are either too simplified and don’t account for these parameters or are so expensive that only very few laboratories conduct research with them. Therefore, development of cheap sensors, that can be easily produced, is important to advance research in organ perfusion.
Keywords
Optics, Glucose, Perfusion, Human
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-19 , Earliest start: 2026-02-01 , Latest end: 2026-11-01
Organization Macromolecular Engineering Laboratory
Hosts Binz Jonas
Topics Engineering and Technology
Braided Helical Capacitive Strain Sensor
The aim of the project is to develop a simple fabrication method for braided capacitive strain sensors. This involves wet-spinning stretchable, insulated and conductive fibers, and subsequently braiding them with conductive thread to obtain a capacitive strain sensor. This new production method is expected to streamline the manufacture of highly sensitive strain sensors.
Keywords
wearable, e-textiles, braiding, wet-spinning, capacitive strain sensors
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Master Thesis
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Published since: 2025-12-19 , Earliest start: 2026-01-12 , Latest end: 2026-12-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Kateb Pierre
Topics Engineering and Technology
Subharmonic emissions from acoustically-coupled microbubble clouds
In the medical context, coated microbubbles have the potential to measure the cardiac pressure noninvasively by means of subharmonic emissions. In this study, we aim to study the influence of acoustic coupling between neighboring microbubbles in the amplitude of the subharmonic emissions.
Keywords
Microbubble dynamics, numerical, subharmonic, pressure estimation.
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Semester Project , Bachelor Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-19 , Earliest start: 2026-01-05
Applications limited to ETH Zurich
Organization Group Supponen
Hosts Collado Gonzalo
Topics Engineering and Technology , Physics
Ultrasonic Plasma Atomization of Recycled Aluminum–Carbide Composite Feedstock for Additive Manufacturing
Pre-fabricated aluminum–carbide composite rods produced from recycled aluminum powder are used as feedstock for Ultrasonic Plasma Atomization (UPA). The rods are melted and atomized by the combined action of a plasma jet and ultrasonic excitation, producing rapidly solidified composite powder particles. The resulting powders are collected and characterized in terms of particle size distribution, morphology, and internal microstructure, with particular focus on reinforcement retention and homogeneity. In a secondary step, selected composite wires are further reduced in diameter by rolling to evaluate formability and suitability for wire-based additive manufacturing processes.
Keywords
Ultrasonic Plasma Atomization Aluminum Matrix Composites Additive Manufacturing Powder characterization
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Bachelor Thesis
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Published since: 2025-12-19 , Earliest start: 2026-02-01 , Latest end: 2026-05-31
Organization Advanced Manufacturing Laboratory
Hosts Fichter Pauline
Topics Engineering and Technology
Numerical investigations of the nonlinear coupling between the shape modes and volumetric oscillations of microbubbles
Microbubble dynamics are rich and complex. When they are excited with an ultrasound wave, these can undergo spherical and non-spherical oscillations. Experimental results suggest that non-spherical shape modes can couple with the spherical oscillation, leading to some unexpected behaviors. In this project we aim to numerically investigate this phenomenon.
Keywords
Microbubble, dynamics, partial differential equations, numerical
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-19 , Earliest start: 2026-01-05
Applications limited to ETH Zurich
Organization Group Supponen
Hosts Collado Gonzalo
Topics Mathematical Sciences , Engineering and Technology , Physics
Assessing the acute and long-term effects of an app intervention on stress using multimodal wearable data
This project investigates changes in stress levels over the course of a longitudinal app-based intervention, as well as acute physiological responses during app use. A wide range of physiological signals were recorded using wearable devices to comprehensively capture autonomic regulation and correlates of stress.
Keywords
electrocardiography (ECG), electrodermal activity (EDA), photoplethysmography (PPG), respiration, electroencephalography (EEG), smart-watch, wearable devices, machine learning, artificial intelligence, signal processing, data analysis, stress, sleep
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-18 , Earliest start: 2026-01-05 , Latest end: 2026-12-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Luster Alexandre
Topics Information, Computing and Communication Sciences , Engineering and Technology
Open-Source Physical AI for Bimanual Contact-Rich Tasks
The aim of this work is to advance fundamental problems in physical AI, including coordinated bimanual control, representation and exploitation of contact interactions, and sim-to-real transfer. The project involves commissioning two OpenArm robotic arms in a leader–follower teleoperation setup, followed by the development and evaluation of learning-based bimanual control strategies. You will collect and generate manipulation data both through teleoperation and in simulated environments, and train coordinated bimanual control policies for contact-rich tasks using NVIDIA Isaac Lab or related frameworks. The project provides substantial freedom, allowing you to explore ideas that align with your personal interests. Foreseen applications include dexterous manipulation in manufacturing, household environments, or assistive robotics. Contributions to the OpenArm project are strongly encouraged.
Keywords
AI, Machine Learning, Robotics
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Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-12-18 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization pd|z Product Development Group Zurich
Hosts Gimeno Lucas
Topics Engineering and Technology
Imitation learning in Electronics Disassembly
Disassemblage of Batteries is a challenging task with high variability, due to changing part geometries, corrosion, dirt, etc. The goal of this Thesis is to demonstrate an imitation-learning based disassembly of a PC Mainboard by removing all the cabling with a robot-arm.
Keywords
imitation learning, AI, Machine Learning, Control, Robotics, industry
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Internship , Master Thesis
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Published since: 2025-12-18 , Earliest start: 2025-12-31 , Latest end: 2026-09-30
Organization pd|z Product Development Group Zurich
Hosts Gimeno Lucas
Topics Engineering and Technology
Engineering of a Smart Consumable-Check Module (prototype, hardware, firmware) for innovative diagnostic devices
DiaxxoCare is a Point-of-Care PCR platform designed for professional use in decentralized and resource-limited settings, where robustness against user mistakes is essential. This project develops an implementation-ready checkpoint system that detects missing or incorrectly placed consumables and unsafe device states (e.g., door/lid not closed), guides the user to recover via the UI, and blocks or pauses the workflow when required conditions are not met. The work includes sensor/actuator selection, firmware/software logic, prototype integration, and validation testing to enable fast deployment on commercial devices.
Keywords
Point-of-Care diagnostics; consumable detection; sensors; actuators; embedded systems; firmware; interlocks; human factors; prototyping; verification & validation; medical/veterinary devices; diaxxoCare
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Semester Project , Course Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-12-17 , Earliest start: 2026-01-01 , Latest end: 2026-08-31
Organization Functional Materials Laboratory
Hosts Gregorini Michele
Topics Engineering and Technology
Operator Learning for Plasticity
We aim to explore general strategies that can be applied to operator learning frameworks and are specific to history-dependent material behaviors.
Keywords
Scientific Machine Learning; SciML; Plasticity; Solid Mechanics; Operator Learning; Artificial Intelligence for Science; Machine Learning;
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Semester Project , Master Thesis
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Published since: 2025-12-16 , Earliest start: 2026-03-01
Organization Computational Mechanics Group
Hosts Mousavi Sepehr
Topics Information, Computing and Communication Sciences , Engineering and Technology
Novel wearable kirigami structures for force-based motion monitoring
The aim of this project is to develop auxetic kirigami-inspired molded sensors using flexible substrates, starting with mechanical simulations (FEA) to guide the design. The resulting technology will enable advancements in wearable electronics for precise force-based sensing applications.
Keywords
finite element analysis, wearable, flexible electronics, kirigami, 3D printing, sensor design, wireless communication
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-16 , Earliest start: 2026-01-12 , Latest end: 2026-12-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Kateb Pierre
Topics Engineering and Technology
Agentic AI for Creating Large Solid Mechanics Datasets
We aim to design and create a framework that uses language model agents to create large physics datasets with minimum human intervention or supervision.
Keywords
Solid Mechanics; Material Modeling; Scientific Machine Learning; SciML; Finite element method; Large language models; LLMs; Agentic AI; NLP
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Master Thesis
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Published since: 2025-12-16 , Earliest start: 2026-02-16
Organization Computational Mechanics Group
Hosts Mousavi Sepehr , Massoudi Soheyl
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Temperature-Dependent Mechanic of Highly Entangled Polyacrylamide-Based Hydrogels
This project explores the temperature-dependent mechanical behavior of highly entangled poly(acrylamide-co-oligoethylene glycol acrylate) hydrogels, with the aim of linking experimental stress–strain data to predictive mathematical models for viscoelastic materials. These polymer networks are characterized by high monomer concentrations, low initiator content, and strong topological entanglements, making them an excellent experimental platform for testing modern theories of polymer dynamics. The student will systematically study how mechanical properties such as stiffness, hysteresis, stress relaxation, and nonlinearity evolve with temperature and deformation rate. Mechanical testing will be performed over a controlled temperature range to generate high-quality stress–strain data under compression and, where relevant, cyclic or rate-dependent loading. A central goal is to assess whether existing molecularly informed viscoelastic models can accurately capture the observed behavior, particularly in regimes where entanglements dominate the mechanical response. The project is carried out in close collaboration with a second research group specializing in theoretical and mathematical modeling of soft matter. This provides a rare opportunity to work at the interface between experiment and theory: experimental observations will directly inform model validation, refinement, and parameter selection. The broader motivation is to improve the predictive power of constitutive models for soft, polymer-based materials, which are widely used in applications ranging from adhesives to damping and load-bearing soft solids. This project is well suited for a student who is interested in polymer physics, rheology, or soft-matter mechanics, and who enjoys quantitative thinking. Independence, curiosity, and a willingness to engage with both experiments and theory are essential, as the project offers significant freedom to shape the experimental strategy and contribute original insights.
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Semester Project , Course Project , Internship , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-15 , Earliest start: 2026-02-16
Organization Macromolecular Engineering Laboratory
Hosts Mommer Stefan
Topics Engineering and Technology , Chemistry
Inline Quality Control with image analysis & AI
diaxxo, a start-up from ETH Zürich, is revolutionizing molecular diagnostics with a cutting-edge Point-of-Care PCR device. Their innovative technology facilitates rapid, accurate diagnostic testing across human, veterinary, and food applications, especially in developing countries. The PCR process amplifies DNA sequences to identify pathogens accurately. Key to diaxxo's system are specialized aluminum cartridges containing pre-loaded, dried reagents, essential for precise diagnostics. However, current manufacturing challenges in reagent loading and drying affect cartridge quality. The project aims to develop a Quality Control station using advanced imaging and AI to ensure accurate reagent placement and drying, enhancing diagnostic reliability and effectiveness.
Keywords
Image Analysis, AI Technology, High-Resolution Imaging, Visual Data, Quality Control (QC), Automated Decision Making, Defect Detection, Machine Learning, pattern Recognition, Real-Time Analysis
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-13 , Earliest start: 2024-07-21 , Latest end: 2025-06-30
Organization Functional Materials Laboratory
Hosts Gregorini Michele
Topics Information, Computing and Communication Sciences , Engineering and Technology
Data-driven analysis of railway track condition using real-world and simulated GPR measurements
Ground Penetrating Radar (GPR) is an increasingly important tool for assessing the condition of railway infrastructure, particularly with respect to ballast fouling, contamination, and moisture presence, key indicators of track health and long-term performance. In collaboration with SBB and Terra Vermessungen AG, this master thesis investigates how real-world and simulated GPR data can be used to develop robust, data-driven methods for railway track condition assessment. The student will work with extensive field measurements, apply advanced signal processing and statistical/time-series analysis, and explore machine learning approaches to extract meaningful condition indicators from GPR responses. The work will support ongoing research efforts to better understand subsurface behaviour, enhance interpretation of GPR signals, and contribute to the planning and execution of future measurement campaigns on operational railway lines.
Keywords
Ground Penetrating Radar, railway track condition, ballast fouling, moisture detection, machine learning, signal processing
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Semester Project , Master Thesis
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Published since: 2025-12-12
Organization Structural Mechanics (Prof. Chatzi)
Hosts Arcieri Giacomo
Topics Engineering and Technology
Development of a CO2 Absorption Reactor
Reducing global warming to a minimum requires the deployment of carbon dioxide removal (CDR) technologies to remove CO2 from the atmosphere and compensate for emissions that cannot be completely eliminated. Direct air capture (DAC) with CO2 storage offers a scalable and permanent CDR method. However, DAC is still in its early stages of development. Additionally, high costs, driven in part by significant energy demands, have slowed its widespread adoption. Accelerating research into alternative, energy-efficient approaches is critical to DAC overcoming these barriers and enabling large-scale deployment.
Keywords
CO2, Absorption, Technology, Engineering
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Master Thesis
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Published since: 2025-12-12 , Earliest start: 2026-02-01 , Latest end: 2026-09-30
Organization Laboratory for Electrochemical Energy Systems
Hosts Jauer Marius
Topics Engineering and Technology
Model Compression using the Information Bottleneck Principle for Medical AI and wearable devices
This project investigates the use of the Information Bottleneck (IB) theory as a framework for deep neural network compression, aiming to enhance the deployment of medical AI systems in computationally constrained environments. By quantifying and optimizing the trade-off between information preservation and redundancy, this project explores how IB-based compression can maintain model accuracy while significantly reducing computational load — enabling efficient and scalable medical image segmentation and classification in healthcare applications.
Keywords
machine learning, artificial intelligence, medical AI, information bottleneck, information theory, theoretical machine learning, model compression, deep learning, information theory, U-Net, Vision Transformer (ViT), wearable devices
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Master Thesis
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Published since: 2025-12-12 , Earliest start: 2026-01-01 , Latest end: 2026-10-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Information, Computing and Communication Sciences , Engineering and Technology
Let the cells dance!
Dermal Fibroblasts are resident cells in the thickest layer of the skin. They are thought to be sparsely spread out, happily hanging out in their neighborhood. In vitro, we simplify the physiological situation by culturing the cells on 2D substrates to enable us to study them under distinct stimuli. One of which is the stiffness of the matrix that the cells attach to (mimicking for example stiff extracellular matrix of wounded skin vs. soft ECM in healthy skin). Once plated on the substrates, the cells spread and thereby test the substrate stiffness by forming focal adhesions and pulling by contraction, which we can visualize by microscopy imaging after several hours. Dermal Fibroblasts are resident cells in the thickest layer of the skin. They are thought to be sparsely spread out, happily hanging out in their neighborhood. In vitro, we simplify the physiological situation by culturing the cells on 2D substrates to enable us to study them under distinct stimuli. One of which is the stiffness of the matrix that the cells attach to (mimicking for example stiff extracellular matrix of wounded skin vs. soft ECM in healthy skin). Once plated on the substrates, the cells spread and thereby test the substrate stiffness by forming focal adhesions and pulling by contraction, which we can visualize by microscopy imaging after several hours.
Keywords
Mechanobiology, Cell Culture, Live Cell Imaging Expereriments, Image Analysis, Coding
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Semester Project , Internship , Lab Practice , Bachelor Thesis , Master Thesis
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Published since: 2025-12-12 , Earliest start: 2026-01-05 , Latest end: 2026-07-31
Organization Experimental Continuum Mechanics
Hosts Kromer Daniela
Topics Medical and Health Sciences , Engineering and Technology , Biology
Propagation-Based Phase-Contrast Imaging with Cold Neutrons: Towards Tomographic Imaging of Weakly Absorbing Metallic Objects
Neutron imaging provides unique opportunity for studying technologically and biologically relevant materials as a complementary modality to other techniques. The increased interest in neutron imaging relies on their strong penetration into metallic materials, their sensitivity to light elements, and the possibility of manipulating contrast via isotope substitution. Among the imaging approaches, propagation based phase-contrast imaging recently showed a promising extension to conventional absorption transmission imaging. This method, well established with synchrotron X-ray radiation, relies on a (partially) coherent beam and carefully controlled experimental conditions to convert phase variations of the incoming wavefront into quantitative measurements. Note that this opportunity is for the Institut Laue-Langevin in Grenoble, France.
Keywords
phase-contrast imaging; synchrotron radiation; imaging techniques
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Internship
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Published since: 2025-12-12 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization Group Supponen
Hosts Brewer Cameron
Topics Engineering and Technology
Studying the Stretch Signature of Skin with a Novel Multiplexed Imaging Approach
The skin that wraps our body is constantly subjected to stretch by body movements. To study the stretch signature of the skin, we tested murine stretched skin samples with microindentation and multiplexed imaging. Imaging mass cytometry is a powerful imaging technique where up to 40 markers can be visualized simultaneously. For the first time, this approach allows us to see the microstructure of the skin and with this, study the effects of stretch. In this project we will identify and quantify structural skin properties that are affected by skin stretch. Semi-automated image analysis tools will then be implemented to quantify the skin microstructure under different stretch conditions. These findings we greatly enhance our knowledge of skin, which is needed to optimize treatments like skin expanders.
Keywords
Skin Biomechanics, Imaging Mass Cytometry (IMC), Image Analysis
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Semester Project , Internship , Bachelor Thesis
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Published since: 2025-12-12 , Earliest start: 2025-12-15 , Latest end: 2026-04-30
Organization Experimental Continuum Mechanics
Hosts Kromer Daniela
Topics Medical and Health Sciences , Engineering and Technology , Biology
Implementation of a Quality Management System in a diagnostic startup
The intern/student will support the development and refinement of a practical Quality Management System (QMS) for point-of-care PCR devices and cartridges. The focus is on product and process risk analysis, definition of critical quality control points, and implementation of robust documentation, traceability, and non-conformance management to ensure reliable, high-quality diagnostic products in an industrial start-up environment.
Keywords
Quality Management System, Quality Control, Risk Management, PCR Devices, Cartridges, SOPs, Traceability, Non-Conformance, Diagnostics, Manufacturing
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-12-11 , Earliest start: 2026-01-01 , Latest end: 2026-09-01
Organization Functional Materials Laboratory
Hosts Gregorini Michele
Topics Engineering and Technology , Commerce, Management, Tourism and Services , Chemistry
Master Thesis in Learning and Control
We offer a variety of Master Thesis in the topics of Robotics, Learning and Control. Topics include: - imitation learning for cable disassembly - RL-based refinement of imitation learning policies - safe & stable RL and safety filters - encoding high level task primitives with learning policies - 3D and semantic perception of dynamic environments
Keywords
Robotics, Control, Imitation Learning, Reinforcement Learning, Perception, Computer Vision
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Master Thesis
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Published since: 2025-12-11 , Earliest start: 2025-12-31 , Latest end: 2026-09-01
Organization pd|z Product Development Group Zurich
Hosts Gimeno Lucas
Topics Information, Computing and Communication Sciences , Engineering and Technology
Designing a Parametric Software Toolchain for Self-Driving FDM 3D-Printing Laboratories
Self-driving laboratories have shown impressive capabilities in fields such as pharmacy, biology, chemistry, and increasingly in materials discovery, where automated systems execute thousands of experiments with minimal human intervention. Central to these systems is an autonomous design–make–test cycle, in which software and machines interact seamlessly—from parameter selection to fabrication, robotic sample handling, testing, and again parameter optimization. This thesis aims to develop a headless software toolchain that feeds structured and semantic input parameters (high-level geometric parameters) into corresponding parametric CAD models, exports them, configures an automated slicer from the command line, starts print jobs on a real FDM machine, collects test results from a separate testing system, and finally feeds all results into an optimization or decision model that adjusts the input parameters for the next iteration.
Keywords
Design automation, additive manufacturing, 3D-printing, FDM, Slicer, self-driving laboratory (SDL), Prusa XL, FreeCAD, Grasshopper, Closed-loop optimization
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-11 , Earliest start: 2026-02-01 , Latest end: 2026-06-30
Organization pd|z Product Development Group Zurich
Hosts Stein Tom
Topics Engineering and Technology
Multimodal Deep Learning for Gaze-Driven Step Recognition in Orthopedic Training
This project investigates how combining egocentric video with eye-tracking data can improve automated step segmentation in a simulated orthopedic procedure. Using pretrained visual feature extractors and temporal models such as TCNs or Transformers, we aim to predict fine-grained surgical actions and evaluate the added value of gaze information. The goal is to enhance workflow understanding, interpretability, and objective feedback in surgical training.
Keywords
Eye-tracking, Egocentric video, Step segmentation, Orthopedics, Machine Learning, Transformers, Convolutional Neural Networks
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Semester Project , Master Thesis
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Published since: 2025-12-11 , Earliest start: 2026-01-05 , Latest end: 2026-12-31
Organization pd|z Product Development Group Zurich
Hosts Hogenkamp Maarten
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Informed Exploration in Reinforcement Learning via Sampling-Based Planning
Robust locomotion across diverse terrains remains one of the most challenging and exciting problems in legged robotics. While deep reinforcement learning (RL) has enabled impressive quadrupedal behaviors, generalization to unseen or complex terrains often suffers from low sample efficiency. To address this, researchers typically rely on labor-intensive curriculum design, where training terrains are manually structured to progress from easy to difficult, while trying to avoid catastrophic forgetting. These staged curricula allow the RL agent to master simple environments before tackling more complex ones. However, even with such manually designed curricula, RL training can take several days. This is partly because the agent does not retain knowledge about where it has succeeded or failed, nor does it use this experience to inform future exploration. This project aims to develop an automated approach to guide the RL exploration by leveraging sampling-based planning techniques. We formulate the training process as a graph expansion problem, wherein the terrain space is incrementally explored to maximize gains in locomotion robustness and performance. Can the Voronoi bias inherent in sampling-based planning steer the agent toward more effective and sample-efficient training trajectories? If successful, this approach could enable the use of real-world terrain scans for locomotion training, reducing dependence on expert-designed environments and substantially accelerating the training process. The project brings together concepts from sampling-based planning, adaptive curricula, and locomotion learning.
Keywords
Curriculum Learning, Quadruped Locomotion, Sampling-Based Planning, Reinforcement Learning
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Semester Project , Master Thesis
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Published since: 2025-12-10
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , University of Zurich
Organization Robotic Systems Lab
Hosts Schwarke Clemens , Klemm Victor , Qu Kaixian
Topics Information, Computing and Communication Sciences
Simulator-Based Study of Camera Monitor Systems for Pedestrian Detection in Mobile Machinery
This project will develop and use a high-fidelity simulator to study how professional mobile-machine operators use Camera Monitor Systems (CMS) to detect pedestrians in hazardous zones. The student will help design and run an experimental study in which operators complete realistic trenching tasks using a virtual excavator while monitoring CMS feeds for pedestrians and responding to hazards. The data will then be used to develop a machine learning (ML) model that can predict safety performance and inform future CMS design.
Keywords
virtual reality; simulator study; Unity; eye-tracking; machine learning for safety and health;
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Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-12-10 , Earliest start: 2025-12-10 , Latest end: 2026-10-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin , Otesteanu Corin, Dr
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences
Sign Language Interpreter
Sign language interpretation ensures communication remains inclusive, yet it is currently a task restricted to human experts. While modern humanoid hardware finally has the finger and arm dexterity to perform manipulation tasks, research exploring its applications in sign language communication is limited. We propose developing a control algorithm capable of listening to spoken language and translating it into sign language on a physical robot to act as an interpreter. In this project, you will focus on dynamic motion generation using reinforcement learning. This includes a variety of challenges from fields, requiring arm motion reconstruction from video, retargeting these poses to the robot’s morphology, training a robot to recreate these kinematic states, and then developing a method to receive text input to smoothly access this built motion vocabulary. You will then design a pipeline that can receive audio input from an interlocutor and feed these to the policy in real-time to effectively interpret the speech into sign language. You will be tackling challenges such as ensuring that words are being clearly formed by the robot and enabling smooth transitions between words.
Keywords
Humanoid robotics, learning from demonstration, reinforcement learning
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Semester Project , Master Thesis
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Published since: 2025-12-10
Organization Robotic Systems Lab
Hosts Wang Shengzhi , Mittal Mayank , Heyrman Matthias
Topics Information, Computing and Communication Sciences , Engineering and Technology
Predicting muscle forces from spinal alignment with machine learning - towards biomechanics-informed preoperative planning
How does patient alignment influence paraspinal muscle forces? In this project, we will explore these relationship analysing existing data and establishing a machine learning model to replace complex patient analyses, and bring biomechanics closer to clinical practise.
Keywords
Spine biomechanics, statistical analysis, machine learning
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Semester Project , Bachelor Thesis
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Published since: 2025-12-10 , Earliest start: 2026-01-01 , Latest end: 2026-07-31
Organization Ferguson Group / Laboratory for Orthopaedic Technology
Hosts Ignasiak Dominika
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Gaussian Splatting Super Resolution
Radiance fields like 3D Gaussian Splatting enable fast, high-fidelity scene reconstruction from real-time data. However, reconstruction quality improves in noticeable stages—e.g., coarse at 500 epochs, detailed at 5000. This project explores whether AI-based upscaling and denoising techniques can be used to predict and accelerate these improvements during training. By anticipating reconstruction quality transitions, we aim to reduce training time while maintaining visual fidelity—advancing the efficiency of radiance field learning.
Keywords
Gaussian Splatting, Computer Vision, Reconstruction
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Master Thesis
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Published since: 2025-12-09 , Earliest start: 2025-11-01 , Latest end: 2026-07-31
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Patil Vaishakh , Wilder-Smith Max
Topics Information, Computing and Communication Sciences
Walking Through Fog with Radar Splatting and RL
Help push the boundaries of robotic perception in foggy and visually degraded environments. This project focuses on enhancing the navigation capabilities of the quadruped robot Anymal using radar to perceive through fog. You'll simulate challenging conditions in NVIDIA IsaacLab and IsaacSim, generate clear 3D maps using 3D Gaussian Splatting, and train reinforcement learning-based navigation policies for real-world deployment. Combining advanced sensor fusion with cutting-edge RL, this project offers a hands-on opportunity to explore next-gen robotic vision and autonomy.
Keywords
Gaussian Splatting, Robotics, RL,
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Master Thesis
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Published since: 2025-12-09 , Earliest start: 2025-11-01 , Latest end: 2026-07-31
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Wilder-Smith Max , Patil Vaishakh , Roth Pascal
Topics Information, Computing and Communication Sciences
Propose Your Own Robotics Project
This project invites you to step into the role of an innovator, encouraging you to identify challenges you are passionate about within the field of robotics. Rather than working on predefined problems, you will have the freedom to propose your own project ideas, address real-world issues, or explore cutting-edge topics. This project allows you to define your own research journey.
Keywords
Robotics, Research
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-09 , Earliest start: 2025-01-27
Organization Robotic Systems Lab
Hosts Schwarke Clemens , Bjelonic Filip , Klemm Victor
Topics Information, Computing and Communication Sciences
Computational Modeling of Muscle Dynamics for Biohybrid Robots
This research aims to advance biohybrid robotics by integrating living biological components with artificial materials. The focus is on developing computational models for artificial muscle cells, a critical element in creating biohybrid robots. Challenges include modeling the complex and nonlinear nature of biological muscles, considering factors like elasticity and muscle fatigue, as well as accounting for fluid-structure interaction in the artificial muscle's environment. The research combines first principle soft body simulation methods and machine learning to improve understanding and control of biohybrid systems.
Keywords
Biohybrid Robotics, Computational Models, Soft Body Simulation, Finite Element Method (FEM), Muscle Dynamics, Soft Robotics
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-09 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization Soft Robotics Lab
Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Biology , Physics
GPU Acceleration of Soft Robot Modeling: Enhancing Performance with CUDA
We are enhancing soft robot modeling by developing a GPU-accelerated version of our FEM-based framework using CUDA. This research focuses on optimizing parallel computations to significantly speed up simulations, enabling larger problem sizes and real-time control. By improving computational efficiency, we aim to advance soft robotics research and facilitate more detailed, dynamic simulations.
Keywords
Soft Body Simulation, high-performance computing, GPU programming, Parallel Computing, Finite Element Method (FEM), Multiphysics Simulation
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-09 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization Soft Robotics Lab
Hosts Katzschmann Robert, Prof. Dr. , Mekkattu Manuel
Topics Information, Computing and Communication Sciences , Engineering and Technology
Precision Positioning System for Miniature Specimens
This thesis develops an enhanced high-precision positioning concept for miniature tension test specimens by drawing on techniques from PCB assembly, micro-manipulation, and camera-based vision systems. The implemented approach is validated through prototype testing, demonstrating improved alignment accuracy and reproducibility compared to the current setup.
Keywords
Computer vision; Precision alignment; Micro-scale automation; Fiducial detection; Miniature specimen handling
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-09 , Earliest start: 2026-01-05 , Latest end: 2026-10-31
Organization Computational Modelling of Materials in Manufacturing
Hosts Zwicker Ruben , Koltzenburg Nils
Topics Information, Computing and Communication Sciences , Engineering and Technology
Advancing Soft Robot Modeling: Integrating Physics, Optimization, and Control
We are advancing soft robot simulation with FEM and energy-based methods to model complex, adaptive behaviors. This research entails developing the framework to support diverse designs, integrate new physics models, and optimize performance, enabling enhanced control and real-world applications of soft robots.
Keywords
Soft Robotics, Finite Element Method (FEM), Physical Modeling, Benchmarking, Optimization, Multiphysics Simulation, Sim-to-Real
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-09 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization Soft Robotics Lab
Hosts Mekkattu Manuel , Katzschmann Robert, Prof. Dr.
Topics Information, Computing and Communication Sciences , Engineering and Technology
Software Development: Enabling In Vitro Neuroscience Research
This project focuses on developing software for advanced neural interfaces used in in vitro studies. These interfaces enable precise exploration of neural activity, providing critical insights into neuronal dynamics, drug interactions, and neurological disorders. The project involves creating and optimizing software for data acquisition, analysis, and visualization, which directly enhances the usability and impact of these tools in research and healthcare applications. Ideal candidates will possess strong programming skills in Python. This project is available as Master thesis or semester project.
Keywords
Software development; Neural Interfaces; Neuroscience; Python; Biomedical Research; Neuroengineering; Neurotechnology.
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Semester Project , Internship , Master Thesis
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Published since: 2025-12-08 , Earliest start: 2025-12-14
Organization Bio Engineering Laboratory
Hosts Cardes Fernando
Topics Information, Computing and Communication Sciences
Multistable robotic tensegrities for dynamic shape-shifting
This thesis will combine robotic hardware prototyping with rigorous first principles-based modeling. The goal: tap into tensegrities’ nonlinear properties, such as multistability and instability, to realize robotic modules (bodies, arms, legs, etc.) that form the basis of dynamic shape-shifting systems.
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Master Thesis
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Published since: 2025-12-04 , Earliest start: 2026-01-01 , Latest end: 2026-08-01
Organization Robotic Systems Lab
Hosts Baines Robert
Topics Information, Computing and Communication Sciences , Engineering and Technology
Generative Environment Design: Using LLMs to bridge Sim-to-Real Gap for Locomotion
This project proposes an LLM-driven framework to automate the design of complex simulation environments for robust legged locomotion. By translating natural language descriptions directly into low-level physics parameters, we replace tedious manual tuning with semantic reasoning. The study focuses on training adaptive policies for quadrupedal or wheeled-legged robots, aiming to achieve robust performance across diverse, language-generated terrains.
Keywords
Large Language Models, Locomotion, Sim-to-Real, Domain Randomization, Physics Simulation, Reinforcement Learning.
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-12-03
Organization Robotic Systems Lab
Hosts Palma Emilio , Roth Pascal
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Physics
Evaluation of muscle fatigue on paraspinal muscle activation patterns and spinal loads in patients with lumbar spinal stenosis
Lumbar spinal stenosis (LSS) is a condition characterized by a narrowing of the spinal canal, which can lead to compression of the lumbosacral nerve roots and/or the cauda equina. Clinical observations show that patients often adopt alternative postures and movement strategies to enlarge the spinal canal and relieve pain. These compensations likely require elevated paraspinal muscle activation may increase spinal segmental loads. Muscle fatigue may further increase compensatory posture, joint load and pain representing a vicious cycle. However, the specific implications of muscle fatigue on spinal loading in individuals with LSS remains insufficiently understood. The objective of this master thesis is to investigate how trunk muscle fatigue influences muscle recruitment patterns and spinal segmental loads in individuals with LSS. For this purpose, clinical data from 120+ patients with LSS - collected before and after a fatigue protocol - will be used to drive dynamic simulations of a full-body musculoskeletal model in the AnyBody Modeling System software.
Keywords
Spine biomechanics, musculoskeletal modeling, fatigue, trunk muscles
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-02 , Earliest start: 2026-02-01 , Latest end: 2026-07-31
Organization Musculoskeletal Biomechanics
Hosts Caimi Alice
Topics Engineering and Technology
Reinforcement Learning for Excavation Planning In Terra
We aim to develop a reinforcement learning-based global excavation planner that can plan for the long term and execute a wide range of excavation geometries. The system will be deployed on our legged excavator.
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Keywords: Reinforcement learning, task planning
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Semester Project , Master Thesis
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Published since: 2025-12-01 , Earliest start: 2026-02-01 , Latest end: 2026-09-30
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Foundation models for generalizable construction machine automation
Autonomous operation of heavy construction machinery promises major gains in safety, efficiency, and scalability for the multi-trillion-dollar construction industry. Excavators present a unique challenge, combining the navigation demands of autonomous driving with the precision of robotic manipulation in unstructured, dynamic environments. This project explores Vision-Language-Action (VLA) and diffusion-based policy learning to develop generalizable excavation policies. Leveraging large-scale demonstration data naturally collected during human operation, we aim to train multimodal control models capable of adapting across sites, lighting conditions, and machine types. The approach will be evaluated through simulation benchmarks and, if possible, real-world trials, advancing the path toward scalable, generalist autonomy for robotic construction.
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Semester Project , Master Thesis
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Published since: 2025-12-01 , Earliest start: 2025-08-31 , Latest end: 2026-03-31
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne
Organization Robotic Systems Lab
Hosts Nan Fang , Zhang Weixuan
Topics Engineering and Technology
Perceptive Generalist Excavator Transformer
We want to develop a generalist digging agent that is able to do multiple tasks, such as digging and moving loose soil, and/or control multiple excavators. We plan to use a decoder only GPT model, trained on offline data and potentially online RL as posttraining, to accomplish these tasks.
Keywords
Offline reinforcement learning, transformers, autonomous excavation
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Semester Project , Master Thesis
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Published since: 2025-12-01 , Earliest start: 2026-02-01 , Latest end: 2026-10-31
Organization Robotic Systems Lab
Hosts Werner Lennart , Terenzi Lorenzo , Nan Fang
Topics Information, Computing and Communication Sciences
Reinforcement Learning for Particle-Based Excavation in Isaaclab / Newton
We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaaclab and Newton.
Keywords
particle simulation, omniverse, warp, reinforcement learning
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Semester Project , Master Thesis
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Published since: 2025-12-01 , Earliest start: 2025-06-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Information, Computing and Communication Sciences
Automated Design and Additive Manufacturing of Bending Jigs for Induction Coil Fabrication
Induction heating is used in soldering applications where fast, efficient and localized heating is necessary. Examples include the repair of photovoltaic modules and soldering of smart textiles. Heat is introduced in the solder joint through electromagnetic induction, where high frequency excitation of a coil is used to induce current in the solder pad. Coil for these applications are often bent from copper tube, to allow for internal water cooling. Coils are often application-specific and therefore manually produced by bending. This process depends on a skilled fabricator, and results are often not reproducible. The idea of this thesis is to use automatically generated bending jigs that can be additively manufactured. A design automation workflow should be developed that generates the necessary jigs based on a given coil geometry without manual intervention. The jigs should then be evaluated by using them to manufacture various coils.
Keywords
Design automation, additive manufacturing, 3D-printing, induction heating, hands-on
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-01
Organization pd|z Product Development Group Zurich
Hosts Ritter Simon
Topics Engineering and Technology
Self-Supervised LiDAR–RGB Encoders for Autonomous Earthworks
This project adapts recent self-supervised 3D and 2D–3D representation learning methods (Sonata/Concerto-style encoders) to build a robust LiDAR–RGB backbone for earthmoving robots. The goal is a reusable encoder that powers perception for excavation, loading, traversability, and safety on real construction sites, and runs in real time on our robots.
Keywords
LiDAR–RGB fusion, Self-supervised learning, 2D–3D representations, Earthmoving robotics, Perception
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Semester Project , Master Thesis
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Published since: 2025-12-01 , Earliest start: 2026-02-01 , Latest end: 2026-08-31
Organization Robotic Systems Lab
Hosts Terenzi Lorenzo
Topics Engineering and Technology
RL Finetuning for Generalized Quadruped Locomotion
This project investigates the potential of reinforcement learning (RL) fine-tuning to develop a single, universal locomotion policy for quadruped robots. Building on prior work in multi-terrain skill synthesis [1], we will probe the limits of generalization by systematically fine-tuning on an ever-expanding set of diverse environments. This incremental approach will test the hypothesis that a controller can learn to robustly navigate a vast range of terrains. As a potential extension, procedural terrain generation may be used to automatically create novel challenges, pushing the boundaries of policy robustness.
Keywords
Reinforcement Learning, Quadruped Locomotion
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Master Thesis
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Published since: 2025-11-28 , Earliest start: 2025-06-15
Organization Robotic Systems Lab
Hosts Schwarke Clemens , He Junzhe
Topics Information, Computing and Communication Sciences
Hardware Support HiWi
Mechanical Design, Integration, Robot repairs
Keywords
Hardware, Design, Mechanics, CAD
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Student Assistant / HiWi
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Published since: 2025-11-28 , Earliest start: 2025-12-01
Organization Robotic Systems Lab
Hosts Krasnova Elena
Topics Engineering and Technology
Data-Driven Health Indicators and RUL Forecasting for Mechanical Systems
This thesis explores data-driven methods for assessing the health and forecasting the remaining useful life (RUL) of complex mechanical systems using benchmark datasets such as NASA C-MAPSS, N-C-MAPSS, FEMTO/PRONOSTIA and XJTU-SY. The student will develop health indicators by modelling nominal system behaviour with recurrent and operator-learning architectures, and use these indicators to track degradation over time. Building on this, the project involves training uncertainty-aware RUL models and evaluating their calibration, interpretability, and suitability for deployment. The outcome is an integrated predictive-maintenance workflow combining health assessment, degradation tracking, and reliable RUL forecasting.
Keywords
predictive maintenance, remaining useful life, neural operators, condition monitoring, degradation modelling
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-27 , Earliest start: 2026-01-15 , Latest end: 2026-08-31
Organization Structural Mechanics (Prof. Chatzi)
Hosts Chatzi Eleni
Topics Engineering and Technology
Mechanophores for advanced wearable strain and pressure sensors
The goal of the project is to synthesize and characterize a number of small molecules capable of acting as mechanophore addition to various polymers. These polymers would then be used as wearable strain or pressure sensors.
Keywords
mechanophore, polymer, wearable, sensor, color, strain, pressure
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Master Thesis
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Published since: 2025-11-27
Organization Biomedical and Mobile Health Technology Lab
Hosts Shokurov Aleksandr
Topics Engineering and Technology , Chemistry
Hybrid Modeling for Twinning and Structural Health Monitoring in Engineered Systems
Ensuring the safe, efficient, and resilient operation of structural assets throughout their life cycle relies on the integration of sensing data with computational models that are both rapid to evaluate and reliable. This hybrid paradigm is particularly vital in the operation and maintenance of structures that operate under high variability and may experience damage or extreme events that push their response far beyond design assumptions. In this context, this thesis will focus on deriving actionable and flexible hybrid representations and demonstrate the potential they offer towards digital twinning offer for the optimized operation & maintenance of real-life structural systems.
Keywords
Structural Health Monitoring; Digital Twins; Machine Learning; Surrogate Modelling; Data Assimilation; Inverse Problems;
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-27 , Earliest start: 2026-02-01 , Latest end: 2026-08-31
Organization Structural Mechanics (Prof. Chatzi)
Hosts Vlachas Konstantinos , Chatzi Eleni
Topics Engineering and Technology
Augmented Reality-assisted Finite Element Analysis
Augmented reality (AR) has revolutionized the video game industry via developing interactive, three-dimensional visualizations of physical processes or life-like environments. Building upon existing tools and previous project work, the aim of this thesis is twofold: First, to develop a visualization pipeline that allows users to experience and assess Finite Element Analysis results in an immersive, holographic environment. Second, to enable user interaction with the modeling software via the AR environment, thus enabling the user to calibrate the underlying model or request additional parametric analyses.
Keywords
Augmented Reality; Structural Dynamics; Finite Element Analysis;
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Semester Project , ETH Zurich (ETHZ)
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Published since: 2025-11-27 , Earliest start: 2026-02-01 , Latest end: 2026-08-31
Organization Structural Mechanics (Prof. Chatzi)
Hosts Chatzi Eleni , Vlachas Konstantinos
Topics Engineering and Technology
Point-of-Care Sensor for Urinary Iodine
The goal of the project is to develop a cheap and disposable sensor capable of determination of iodine levels in human urine for early diagnostic purposes.
Keywords
electrochemistry, iodine, nutrition, health, point of care
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Master Thesis
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Published since: 2025-11-27
Organization Biomedical and Mobile Health Technology Lab
Hosts Shokurov Aleksandr
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
Close-Proximity Human-Aware Locomotion
In order to safely navigate a quadrupedal robot through a dense crowd, two conditions need to be satisfied: (1) The robot body does not collide with any of the people in the scene, and (2) the robot does not step on anyone’s feet. The goal of this thesis is to train a locomotion policy that can safely traverse environments with dynamically moving bodies. The problem is treated as an inverse stepping-stone problem, using binary segmentation of the human (foot) areas to create forbidden zones within the elevation map.
Keywords
Robotics, Reinforcement Learning, Crowd Navigation, Human-Robot Interaction
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Master Thesis
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Published since: 2025-11-27 , Earliest start: 2026-02-01 , Latest end: 2026-10-31
Organization Robotic Systems Lab
Hosts Scheidemann Carmen
Topics Information, Computing and Communication Sciences
Engineering of Gastroretentive Drug Delivery systems
Polymer-based drug delivery systems play a central role in shaping modern therapeutics, offering controlled release behavior and improved patient compliance. Yet traditional formulation development still relies largely on resource-intensive and time-consuming iterative experimentation to balance the complex interactions between polymer composition, processing parameters, and drug release behavior. This project aim to solve these limitations by developing a machine learning (ML) algorithm to accelerate the rational design of polymer formulations tailored to specific release profiles. By integrating active ingredient’s encapsulation studies, rheological and mechanical analyses, and detailed release-kinetic profiling, the work aims to build a comprehensive understanding of how formulation variables govern functional performance. The resulting dataset will later support data-driven modelling, enabling faster identification of promising compositions. This approach not only streamlines pharmaceutical development but also advances sustainable practices by minimizing material waste, positioning data-driven formulation as a cornerstone of next-generation smart therapeutics. This project focuses on the optimization and characterization of a novel gastroretentive drug delivery system (GARD) loaded with a selection of active compounds from a pre-established library of molecules. Comprehensive chemical and mechanical analyses will be conducted, encompassing encapsulation efficiency, rheological behavior, drug release kinetics, and the stability of encapsulated active pharmaceutical ingredients (APIs). A curated dataset of API-loaded polymer formulations and their associated properties will be later used to train predictive models, enabling the identification of optimal formulations with tailored release profiles.
Keywords
Drug Delivery Polymer formulation Advanced manufacturing Machine learning
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Semester Project , Internship , Master Thesis
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Published since: 2025-11-26 , Earliest start: 2025-12-01 , Latest end: 2026-12-31
Applications limited to Balgrist Campus , EPFL - Ecole Polytechnique Fédérale de Lausanne , ETH Zurich , Fernfachhochschule , Zurich University of Applied Sciences , University of Zurich , University of Basel , University of Berne , Institute for Research in Biomedicine , Hochschulmedizin Zürich , Empa
Organization Macromolecular Engineering Laboratory
Hosts Guzzi Elia
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
Exploring Applications of Physical Computing to Condition and Structural Health Monitoring
This thesis explores the emerging field of physical computing for condition and structural health monitoring. Recent advances in mechanical metamaterials and MEMS devices have enabled physical signal processing, where a device’s intrinsic dynamics—such as resonance responses—are used to classify complex acoustic inputs with near-zero power consumption. Building on this concept, the project investigates how acoustic emission (AE) signals from damage in composite structures can be identified and classified using MEMS-based physical computing architectures. The student will analyze real AE datasets, extract key signal features, and develop an in-silico training and validation environment for a mechanical classifier. Ultimately, this work contributes toward low-cost “smart-dust” devices capable of passively monitoring structural integrity when remotely interrogated.
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-26 , Earliest start: 2026-02-01 , Latest end: 2026-08-31
Organization Structural Mechanics (Prof. Chatzi)
Hosts Chatzi Eleni
Topics Engineering and Technology
Free-Viewpoint Teleoperation via Dynamic Gaussian Splatting
Immersive teleoperation should feel natural and precise—like reaching in with your own hands. Most prior work shows this only in static scenes, where the operator guides a robot to an object without truly changing the world [1]. Real tasks aren’t that simple: the moment you grasp, move, or reorient something, the scene changes. If the 3D view doesn’t update, depth cues fade, confidence drops, and mistakes creep in. We propose a single-arm teleoperation system that keeps the 3D world live. Using 3D Gaussian Splatting, the scene is continuously refreshed as objects move, so what you see in VR matches what the robot sees right now. With just a wrist camera and small, smart arm adjustments to avoid occlusions (no extra camera arm), the operator keeps a clear view of the action. In VR, you can pick helpful viewpoints on the fly, working with a photorealistic, always-current reconstruction that boosts precision, speed, and confidence. Moreover, you will get hands-on time with the real robot (you really do get to play with it), with proper safety and supervision. Strong results may also lead to a conference or journal paper submission at the end of the project.
Keywords
Dynamic Gaussian Splatting, Teleoperation, Robotics
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Semester Project , Master Thesis
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Published since: 2025-11-25 , Earliest start: 2025-12-01 , Latest end: 2026-06-01
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Wilder-Smith Max , Wang Shengzhi , Patil Vaishakh
Topics Information, Computing and Communication Sciences , Engineering and Technology
Design and control of a bio-inspired tensegrity robot leg
This hardware-focused thesis will build a robotic leg from tensegrity structures, taking the first steps to realizing a new class of dynamic legged robot.
Keywords
Robotics, Quadrupeds, Control, Tensegrity, Mechanics, Design
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-11-25 , Earliest start: 2026-01-01 , Latest end: 2026-11-01
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Baines Robert
Topics Information, Computing and Communication Sciences , Engineering and Technology
Spatial Proteomics of Mechanically-Driven Bone Healing
Bone healing is profoundly influenced by its mechanical environment. Advances in spatial proteomics now allow us to map protein expression within intact tissue and directly relate it to local biomechanical cues. The Laboratory for Bone Biomechanics is developing a new line of research within spatial mechanomics (DOI: 10.1126/sciadv.adp8496), integrating spatially resolved proteomic data with in silico models of the mechanical environment at fracture sites. This approach enables us to investigate, at cellular resolution, how mechanical forces shape protein-level signalling during bone repair.
Keywords
Bone, Mechanobiology, Spatial Proteomics, Protein Expression, Aging, Sex Differences, Mechanical Loading, Finite Element Modelling, Image Analysis
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-11-23 , Earliest start: 2025-12-01 , Latest end: 2026-12-31
Organization Müller Group / Laboratory for Bone Biomechanics
Hosts Mathavan Neashan
Topics Medical and Health Sciences , Engineering and Technology , Biology
Tactile Sensing and Model-Based RL for Contact-Aware Control in Soft Robots
Soft robotic manipulators excel in safe, compliant motion, but controlling them during contact-rich interactions remains a major challenge. This project aims to develop contact-aware control for a tendon-driven soft robotic arm by combining vision-based tactile sensing with model-based reinforcement learning (MBRL).
Keywords
soft robotics, tendon-driven actuation, capacitive sensing, model-based RL, contact-rich control
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-19 , Earliest start: 2026-01-15 , Latest end: 2026-12-31
Organization Soft Robotics Lab
Hosts Zheng Hehui
Topics Information, Computing and Communication Sciences , Engineering and Technology
Reduced-Order Modeling for Density-Based Topology Optimization
This Master's Thesis opportunity is jointly offered by the Chair of Structural Mechanics & Monitoring at ETH Zürich (Prof. Dr. Eleni Chatzi) and by the Group of Engineering Dynamics at ETH Zürich (Dr. Paolo Tiso). Topology optimization is a powerful tool for determining optimal material distribution, but its iterative nature leads to substantial computational costs, especially for large-scale problems. On the other hand, its high-dimensional design space poses unique challenges to apply conventional surrogate modeling techniques, such as Reduced-Order Models. This thesis investigates methodologies to tackle these challenges, thus providing a framework for accelerated topology optimization routines.
Keywords
Reduced-Order Modeling, topology optimization, surrogate models, machine learning
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Master Thesis
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Published since: 2025-11-18 , Earliest start: 2026-02-01 , Latest end: 2026-08-31
Organization Structural Mechanics (Prof. Chatzi)
Hosts Chatzi Eleni , Betti Federico , Tiso Paolo
Topics Mathematical Sciences , Engineering and Technology
Mini-muscle gym: Developing a Broad-field Electrical and Mechanical Stimulation Device for Biohybrid Robots
Biohybrid robotics seeks to replace conventional actuator materials with engineered muscle to harness the adaptability and efficiency of biological systems. A major challenge, however, remains the limited force output of engineered skeletal muscle tissues. This project aims to address that limitation through the development of an electrical stimulation system integrated into a muscle-maturation platform ("mini-muscle gym") designed to enhance tissue strength via mechanical and electrical cues. The work will involve circuit and PCB design, implementation within an existing mechanical framework, and close collaboration with tissue engineers to meet biological requirements. The resulting thesis will form an interdisciplinary contribution at the interface of engineering and biology. See attached pdf for further details and references.
Keywords
Biohybrid robotics, soft robotics, circuit design, signal generation, biomaterials, electrical stimulation, mechanical stimulation, actuation, tissue engineering, muscle tissue, muscle cells.
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-11-17 , Earliest start: 2025-11-24 , Latest end: 2026-07-31
Organization Soft Robotics Lab
Hosts Balciunaite Aiste , Paniagua Pablo
Topics Engineering and Technology
Perceptive object pushing with a quadrupedal manipulator
Legged manipulators combine the mobility of legged robots with the dexterous interaction capabilities of robotic arms. Recent research has demonstrated a variety of skills on such systems using reinforcement learning (RL) controllers trained in simulation. In our previous work [1], we showcased contact-rich, non-prehensile mobile manipulation, where a legged robot was able to move and reorient unknown objects through pushing actions. However, this approach depends on an external motion-capture system to track the object’s 6D pose, a major limitation for real-world and field deployment. This project aims to overcome that challenge by developing a perceptive control policy that performs nonprehensile object manipulation using only onboard sensing. A particularly promising direction is to leverage onboard RGB cameras to provide rich visual feedback regarding both the position and orientation of the object in real time [2]. End-to-end RL (perception to action) and/or teacher-student distillation [3] approaches will be investigated. Through this project, the student will gain extensive hands-on experience in RL, sim-to-real transfer, perception for learning-based control and mobile manipulation. References: 1. Dadiotis et al, “Dynamic object goal pushing with mobile manipulators through model-free constrained reinforcement learning”, ICRA 2025 2. Qureshi et al, “SplatSim: Zero-Shot Sim2Real Transfer of RGB Manipulation Policies Using Gaussian Splatting”, ICRA 2025. 3. Singh et al, “DextrAH-RGB: Visuomotor Policies to Grasp Anything with Dexterous Hands”. arXiv 2024.
Keywords
End-to-end RL, Perceptive Manipulation, Mobile Manipulation
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Master Thesis
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Published since: 2025-11-16 , Earliest start: 2026-01-15 , Latest end: 2026-10-31
Organization Robotic Systems Lab
Hosts Bhardwaj Arjun , Dadiotis Ioannis
Topics Information, Computing and Communication Sciences
Response Inference in Evolving Conditions via Hypernetworks and Online Learning
Engineering dynamical systems operate under variability and continuously changing conditions. This poses unique requirements when designing twin representations, necessitating the adaptive updating of underlying models in real-time. This thesis aims to address this challenge via the use of hypernetworks for forecasting under variability and their fusion with online and active learning techniques. Thus, this work focuses on developing efficient update mechanisms that allow already trained and deployed surrogates to adapt to sensing data while minimizing computational cost and required measurements. The framework will be validated on benchmark dynamical systems with time-varying parameters and applied to real-world case studies.
Keywords
Hypernetworks; Scientific Machine Learning; Nonlinear Dynamics; Computational Modeling;
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-14 , Earliest start: 2026-02-01 , Latest end: 2026-08-31
Organization Structural Mechanics (Prof. Chatzi)
Hosts Vlachas Konstantinos , Chatzi Eleni
Topics Engineering and Technology
Push or pull? Unifying mobile manipulation skills for a quadrupedal manipulator
This thesis will focus on unifying multiple different mobile manipulation skills into a single controller for mobile manipulation with a quadrupedal manipulator
Keywords
mobile manipulation, robotics, control, reinforcement learning, quadrupedal manipulation
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Master Thesis
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Published since: 2025-11-14 , Earliest start: 2026-01-07
Organization Robotic Systems Lab
Hosts An Tianxu , Dadiotis Ioannis
Topics Information, Computing and Communication Sciences , Engineering and Technology
Upcycling of Ti machining waste for sustainable solid state (additive) manufacturing—a life cycle analysis
You will evaluate the sustainability impact of novel circular processing routes that convert Ti swarf into low-cost powders for powder-metallurgical manufacturing, e.g., sintering or additive manufacturing, and compare these to standard primary and secondary synthesis routes.
Keywords
additive manufacturing; powder metallurgy; sustainability; life cycle analysis; economics; titanium
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Semester Project , Internship , Bachelor Thesis , Master Thesis , Master Project (D-MATL)
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Published since: 2025-11-13 , Earliest start: 2026-02-01 , Latest end: 2026-12-31
Organization Nanometallurgy
Hosts Reiser Alain
Topics Engineering and Technology , Economics
Computational modeling of reactive multiphase flow processes
This project employs numerical modeling of reactive multiphase flow and transport processes relevant to a wide range of engineering and environmental systems. Using computational fluid dynamics (CFD) and custom numerical tools, the work aims to simulate coupled flow, transport, and reaction phenomena in porous and non-porous materials.
Keywords
Numerical simulations; Flow and transport; Computational fluid dynamics (CFD); Porous media; Building materials; Corrosion; Material degradation; Computational modeling; Reactive processes
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Semester Project , Master Thesis
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Published since: 2025-11-11
Organization Durability of Engineering Materials (Prof. Angst)
Hosts Malenica Luka
Topics Agricultural, Veterinary and Environmental Sciences , Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Earth Sciences , Chemistry , Physics
Characterizing the Contraction Dynamics of Tissue Engineered Skeletal Muscle Constructs for Biohybrid Robots
Soft robotics is moving toward the use of biological materials, such as muscle tissue, to create biohybrid actuators that harness the adaptability and efficiency of living systems. However, the lack of accurate computational models for muscle contraction limits rational design, making development heavily reliant on trial and error. This project contributes to a sim-to-real pipeline for biohybrid muscle design, focusing on fabrication and experimental characterization of actuators. Students will gain experience in skeletal muscle culture, confocal microscopy, calcium imaging, and force measurements, resulting in an interdisciplinary thesis bridging mechanical engineering and biology.
Keywords
Biohybrid robotics, soft robotics, 3D printing, biomaterials, tissue engineering, muscle tissue, muscle cells, bioprinting, biofabrication, electrical stimulation, actuation, material characterization.
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-11-11 , Earliest start: 2025-11-28 , Latest end: 2026-07-31
Organization Soft Robotics Lab
Hosts Balciunaite Aiste , Katzschmann Robert, Prof. Dr.
Topics Engineering and Technology
Learning Dexterous Robotic Manipulation from Human Demonstrations
The goal of this project is to endow a robotic arm-hand system with the ability to complete everyday-life tasks like using tools, opening doors, or assembling equipment. This skill will have important implications across a range of domains, including personal robotics, manufacturing, and fulfillment.
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Master Thesis
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Published since: 2025-11-11 , Earliest start: 2025-11-16 , Latest end: 2026-08-31
Organization Computational robotics laboratory (Prof. Stelian Coros)
Hosts Coros Stelian
Topics Information, Computing and Communication Sciences
3-Dimensional Convolutional Neural Network for semantic segmentation
X-ray micro-computed tomography is an imaging technique enabling interior characterization of material micro-structures. The incident waves penetrate through the sample and are attenuated by the material density to be absorbed by a detector, represented by a quantized greyscale value. By rotating the sample and iteratively recording radiographic projections, internal boundaries between material phases can be retrieved. To recover quantifiable information regarding the sample, it is crucial to accurately perform semantic segmentation on the computed tomographs. Semantic segmentation refers to the categorization of each individual pixel within an image (voxel in 3D) into bins representing the various respective materials within the original data. Semantic segmentation poses relevance to a wide variety of computer vision and image analysis fields including autonomous driving, biomedical diagnosis, and agricultural analytics. Typical semantic segmentation often utilizes regional texture and color analysis or pixel distribution methods (Gaussian mixture and K-means) to determine pixel classification. These methods are highly reliable yet often are not time efficient on large datasets. Additionally, specific tuning is required for differing samples.
Keywords
Machine Learning; X-ray imaging; Material characterization
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Semester Project
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Published since: 2025-11-10 , Earliest start: 2026-01-12 , Latest end: 2026-05-29
Organization Group Supponen
Hosts Brewer Cameron
Topics Engineering and Technology
Catalytic Degradation of PFAS in water
Per- and polyfluoroalkyl substances (PFAS) represent a persistent class of contaminants of emerging concern in water systems, requiring advanced treatment solutions beyond conventional processes. This master’s thesis project investigates catalytic degradation pathways for PFAS in aqueous environments, integrating material synthesis, catalyst characterization, and treatment optimization. Students will fabricate and analyze novel catalyst materials, evaluate degradation performance under varied operational conditions, and assess the system’s applicability using real-water matrices. Conducted at the Australian Centre for Water and Environmental Biotechnology (ACWEB) at The University of Queensland, the project combines material science, environmental engineering, and analytical chemistry to advance PFAS remediation methodologies.
Keywords
PFAS degradation; catalytic treatment; water purification; material synthesis; environmental nanotechnology; LC-MS analysis; fluoride quantification; advanced oxidation; water quality engineering.
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Master Thesis , Other specific labels , ETH Zurich (ETHZ)
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Published since: 2025-11-10 , Earliest start: 2026-01-01 , Latest end: 2026-12-31
Organization Multiscale Robotics Lab
Hosts Gantenbein Valentin
Topics Engineering and Technology
K-wave simulation of non-linear effects on HIFU transducer wave propagation
High intensity focused ultrasound is a non-invasive biomedical treatment for tissue ablation. Through the propagation of high intensity pressure waves, tissue material can be destroyed by thermal effects or cavitation damage in a pulsed signal. The approach is utilized in treatment of tumours in many parts of the body including breast, kidney, liver, and prostate. The high intensity of the incident wave leads to a non-constant speed of sound within the medium generating non-linearity effects on the wave. Wave non-linearity inherently shifts wave energy to higher harmonics, influencing bubble stability and cavitation threshold. A past student project has used K-wave (a Matlab package) to simulate the pressure field of an ultrasound transducer, focusing on signal reflection and distortion resulting from impeding objects within the propagation field. This project builds upon the previously completed work by incorporating non-linearity in the simulation focusing on high intensity burst waves and enables efficient transducer design by simulating the change in the pressure signal as the number of transducer elements and configuration are manipulated.
Keywords
Nonlinear acoustics; Numerical simulation; Code optimization
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Semester Project
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Published since: 2025-11-10 , Earliest start: 2026-01-12 , Latest end: 2026-05-29
Organization Group Supponen
Hosts Brewer Cameron
Topics Engineering and Technology
AI-Based Blood Pressure Estimation from PPG Signals Using Wearable Devices
This project explores the feasibility of measuring blood pressure using pulse travel time (PTT) between two photoplethysmography (PPG) sensors, validated against ground truth blood pressure cuff measurements, employing machine learning and computational models.
Keywords
machine learning, artificial intelligence, generative AI, photoplethysmography (PPG), smart-watch, wearable devices, blood pressure
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Semester Project , Master Thesis
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Published since: 2025-11-06 , Earliest start: 2025-12-01 , Latest end: 2026-09-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Information, Computing and Communication Sciences , Engineering and Technology
Light-Driven CO₂ Capture via a Photodynamic pH-Swing Process
Direct air capture (DAC) of CO₂ is a key technology for achieving carbon neutrality, yet its large-scale deployment is limited by the high energy required for CO₂ release. At the Electrochemical Energy Systems Laboratory (Prof. Maria Lukatskaya), we are developing a novel, sunlight-driven pH-swing process that uses light to modulate solution acidity and minimize energy input for sorbent regeneration. The project focuses on the design, synthesis, and characterization of photoactive merocyanine molecules capable of reversibly altering their protonation state under light irradiation. These compounds enable alternating high- and low-pH conditions in aqueous media, allowing CO₂ capture in the dark and its controlled release upon illumination.
Keywords
Photoacids; Micelles; pH control; CO2 capture; Light-responsive systems
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Master Thesis
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Published since: 2025-11-06
Organization Laboratory for Electrochemical Energy Systems
Hosts Scapin Joseph
Topics Chemistry
Shape oscillations of bubbles on an oscillating surface
When a microbubble resting on a surface is excited around its resonance frequency, the bubble exhibits intense shape deformations. This project aims at designing an experimental setup to capture the surface instabilities of accelerated bubbles.
Keywords
Fluid dynamics, bubbles, instability
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Semester Project , Bachelor Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-06 , Earliest start: 2026-01-01 , Latest end: 2026-06-30
Applications limited to Department of Mechanical and Process Engineering
Organization Group Supponen
Hosts Presse Louan
Topics Engineering and Technology
PCB Design for in Vitro Neural Interfaces
This project centers on designing and developing high-speed printed circuit boards (PCBs) for advanced CMOS microelectrode arrays (MEAs) used in in vitro neuroscience research. These PCBs are critical for interfacing with neural tissue, enabling precise control and data acquisition from high-density electrode arrays. The project involves schematic design, layout, signal integrity optimization, and testing of PCBs operating at ~100 MHz. Ideal candidates will have experience with Altium Designer and a strong foundation in electronics and signal processing.
Keywords
PCB Design; CMOS MEA; Altium; Signal Integrity; Neurotechnology; Neural interface; BCI; Neuroscience
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-10-30 , Earliest start: 2025-10-31
Organization Bio Engineering Laboratory
Hosts Cardes Fernando
Topics Engineering and Technology
Design and Evaluation of a Signature Circuit for Secure Chip Integration
This project focuses on the design and evaluation of a signature circuit intended for secure integration into a chip. The student will explore different architectural interpretations, implement cryptographic primitives such as hashing and encryption, and assess the circuit’s performance and security. The goal is to identify the most effective design for real-world deployment in secure hardware.
Keywords
VLSI; Cryptography; Hardware Security; RTL Design; HDL; Key Management; Secure Systems; Cybersecurity;
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-10-30 , Earliest start: 2025-10-31
Organization Bio Engineering Laboratory
Hosts Cardes Fernando
Topics Information, Computing and Communication Sciences , Engineering and Technology
Spatially-Enhanced Linear-Attention Transformer for End-to-End Navigation
Transformer architectures have proven highly effective in sequence modelling, but their standard self-attention mechanism suffers from quadratic complexity in sequence length. The work by Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention (Katharopoulos et al., 2020) shows how self-attention can be reformulated as kernel feature maps with a linear complexity implementation. Separately, in navigation and robotics, end-to-end learning of navigation policies (e.g., via reinforcement learning) has shown strong promise; however, many architectures (such as standard RNNs) struggle to build spatial memory — that is, integrating observations from different viewpoints into a coherent spatial representation. For example, the recent work Spatially‑Enhanced Recurrent Memory for Long‑Range Mapless Navigation via End‑to‑End Reinforcement Learning (Yang et al., 2025) proposes Spatially-Enhanced Recurrent Units (SRUs) to address this. This motivates the question: can we combine the efficiency and scalability of linear-attention transformers with a spatial-enhancement mechanism tailored for navigation, thereby achieving end-to-end navigation with long-term spatial memory and efficient inference?
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-10-28 , Earliest start: 2025-11-15 , Latest end: 2025-12-15
Organization Robotic Systems Lab
Hosts Yang Fan
Topics Information, Computing and Communication Sciences
Microbubble characterization through acoustic radiation force
Acoustically driven microbubbles could unlock local drug delivery in a clinical setting. This therapy requires a precise characterization of the microbubble volumetric oscillations. This project will investigate an alternative method to characterize the volumetric oscillations indirectly through the acoustic radiation force. For this, the student is expected to conduct experiments and compare them with the predictions from theoretical models.
Keywords
Biomedical, drug delivery, ultrasound contrast agents, physics, experimental
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Semester Project , Master Thesis
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Published since: 2025-10-28 , Earliest start: 2025-12-01
Applications limited to ETH Zurich
Organization Group Supponen
Hosts Collado Gonzalo
Topics Engineering and Technology , Physics
Hand Gesture Recognition Using High-Density Surface Electromyography (HD-sEMG
The project aims to develop machine learning models for real-time hand gesture recognition using high-density surface electromyography (HD-sEMG) signals. This research focuses on improving neuroprosthetic control and rehabilitation by accurately decoding hand movements from HD-sEMG data.
Keywords
HD-sEMG, neuroprosthetics, biosignal monitoring, machine learning, hand gesture recognition, rehabilitation
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ETH Zurich (ETHZ)
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Published since: 2025-10-20
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Gait and Posture Analysis Using Multimodal Data from Smart Walkers
The project aims to develop machine learning models to analyze gait and posture using multimodal data collected from participants using a robotic walker equipped with multiple cameras and inertial sensors. This research focuses on detecting abnormalities in gait patterns and postural control, contributing to the development of rehabilitation and assistive technologies.
Keywords
gait analysis, posture monitoring, smart walker, motion capture, biomechanics, sensor fusion, rehabilitation, inertial sensors
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ETH Zurich (ETHZ)
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Published since: 2025-10-20
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Detection of Cardiovascular Abnormalities from Paper ECG Images Using Deep Learning
This project aims to develop a deep learning algorithm to detect and classify cardiovascular abnormalities directly from paper-based or image-scanned ECGs. By bypassing the need for full digitization, the objective is to enable rapid diagnosis and improve access to cardiovascular healthcare, particularly in resource-limited settings.
Keywords
ECG, cardiovascular disease, image classification, deep learning, global health, medical imaging, underserved populations
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ETH Zurich (ETHZ)
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Published since: 2025-10-20
Organization Biomedical and Mobile Health Technology Lab
Hosts Qi Shuaixin
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Prevention and Treatment of Chronic Intestinal Leakages – Enteroatmospheric Fistulas
Our project aims to develop a novel therapeutic and preventive approach for Enteroatmospheric Fistulas. A first functional prototype has already been developed, and now, we are excited to work with you and advance it further.
Keywords
Surgery, Surgical Technology, Innovation, Materials Science, 3d printing.
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Semester Project , Internship , Master Thesis
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Published since: 2025-10-20 , Earliest start: 2025-11-01 , Latest end: 2027-09-30
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , University of Zurich , Wyss Translational Center Zurich , University of Berne , University of Geneva , University of Basel
Organization Nanoparticle Systems Engineering Laboratory
Hosts Herrmann Inge
Topics Engineering and Technology
Hardware / software development in medtech startup (project / thesis)
diaxxo, a start-up from ETH Zürich, is transforming molecular diagnostics with an innovative Point-of-Care Polymerase Chain Reaction (PCR) device. Designed to accelerate and democratize access to diagnostic testing, our cutting-edge technology can be used across various fields, from human diagnostics to vet and food testing. Our products are also tailored for use in developing countries and resource-limited settings, aiming to bring reliable diagnostics to every corner of the globe. The company offers several projects and thesis opportunities focusing on interfacing computer and camera systems (e.g. controlling Camera Pi from ESP microcontrollers, and integrating hardware and software components to address design and automation challenges.
Keywords
Point-of-Care PCR, Molecular Diagnostics, Embedded Systems, Arducam SPI, Camera Pi ESP Microcontroller, Hardware-Software Integration, Design and Automation Challenges
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-10-15 , Earliest start: 2024-07-01 , Latest end: 2025-06-30
Organization Functional Materials Laboratory
Hosts Gregorini Michele
Topics Information, Computing and Communication Sciences , Engineering and Technology
Smart Microcapsules for Biomedical Advances
This Master's thesis/semester project focuses on the microfluidic fabrication of microcapsules with multi-environmental responsiveness. The aim is to develop microcapsule-based microrobots capable of adapting to various environmental cues. We envision that these microrobots will be used for complex tasks in biomedical applications.
Keywords
Microfluidics, Microcapsules, Microrobotics, Responsive Polymers, Biomedical Engineering
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Semester Project , Internship , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-10-14 , Earliest start: 2026-01-19
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Medical and Health Sciences , Engineering and Technology , Chemistry
Intelligent Micromachines Made from Droplet-Based Factory
We invite applications for a Master's thesis / semester project that focuses on the fabrication of microrobots with custom shapes. Using our developed droplet printing technique, this project will explore how different microrobot shapes, created by different magnetic fields and materials, influence their control behaviors in blood vessels. This research aims to advance biomedical technologies, particularly in targeted drug delivery and minimally invasive procedures.
Keywords
Microrobotics, 4D Printing, Soft Materials, Biomedical Devices
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Semester Project , Master Thesis , Student Assistant / HiWi , ETH Zurich (ETHZ)
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Published since: 2025-10-14 , Earliest start: 2026-02-02
Organization Multiscale Robotics Lab
Hosts Hu Minghan
Topics Engineering and Technology , Chemistry
Wireless Motion and Health Monitoring with Triboelectric Nanogenerators using a Custom Readout Circuit
This project aims to design and realize a custom single-PCB wireless readout circuit optimized for triboelectric nanogenerators (TENGs) for motion and health monitoring. Unlike previous designs that relied on assembling multiple commercial off-the-shelf PCBs, this project will integrate the functionalities of signal conditioning, energy harvesting, and wireless data transmission onto one compact, low-power circuit board). This PCB will be used to facilitate wireless joint angle analysis and fatigue monitoring during repetitive human movements using machine learning and deep learning.
Keywords
TENG, energy harvesting, wireless circuits, PCB design, low-power electronics, sensors, movement, mobile health, wearables
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Semester Project , Master Thesis
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Published since: 2025-10-14 , Earliest start: 2025-10-01 , Latest end: 2026-08-31
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Engineering and Technology
Machine learning for Motion Estimation and Fatigue Monitoring Using Triboelectric Nanogenerators
This project explores the feasibility of using triboelectric nanogenerators (TENGs) for joint angle analysis and fatigue monitoring during repetitive human movements using machine learning and deep learning.
Keywords
machine learning, artificial intelligence, generative AI, triboelectric nanogenerator, joint angle estimation, motion analysis, fatigue
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Semester Project , Internship , Master Thesis
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Published since: 2025-10-14 , Earliest start: 2025-09-01 , Latest end: 2026-08-01
Organization Biomedical and Mobile Health Technology Lab
Hosts Otesteanu Corin, Dr
Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology
Monitoring in-vitro neural network dynamics using microelectrode arrays
Join our interdisciplinary research team to explore the fascinating world of neuronal networks in vitro. These master projects focus on culturing neurons on CMOS-based microelectrode arrays (MEAs) to study their electrophysiological properties. The exact project scope will be tailored to your interests and background, offering a unique opportunity to contribute to cutting-edge neuroscience and bioengineering research.
Keywords
Neuroscience, Cell Culture, CMOS MEA, Electrophysiology, In Vitro Models, Neural Networks, Bioengineering, Neurotechnology
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Semester Project , Internship , Lab Practice , Master Thesis
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Published since: 2025-10-13 , Earliest start: 2025-06-15
Organization Bio Engineering Laboratory
Hosts Cardes Fernando
Topics Medical and Health Sciences , Engineering and Technology , Biology
Microelectronic circuit design for neural interfaces in 0.18um CMOS technology
This project is about the development of integrated circuits to study neurons and neural networks, and may comprise different parts of the design including analog and/or digital microelectronics, PCB design, signal processing and programming.
Keywords
Microelectronics, CMOS, circuit design, electronics, PCB, signal processing, neural interface.
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Semester Project , Internship , Bachelor Thesis , Master Thesis
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Published since: 2025-10-13 , Earliest start: 2022-01-03
Organization Bio Engineering Laboratory
Hosts Cardes Fernando
Topics Engineering and Technology
Learning-based object orientation prediction for handovers
Humans are exceptional at handovers. Besides timing and spatial precision, they also have a high-level understanding of how the other person wants to use the object that is handed over. This information is needed to hand over an object, such that it can be used directly for a specific task. While robots can reason about grasp affordances, the integration of this information with perception and control is missing.
Keywords
Robot-Human Handover, Human-Robot-Interaction, Mobile Manipulation, Robotics
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Semester Project , Master Thesis
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Published since: 2025-10-13 , Earliest start: 2025-02-01 , Latest end: 2025-12-31
Organization Robotic Systems Lab
Hosts Scheidemann Carmen , Tulbure Andreea
Topics Information, Computing and Communication Sciences , Engineering and Technology
Microfabrication and characterization of microelectrodes for neural interfaces
The focus of this project is on the fabrication of microelectrodes for advanced neural interfaces in a cutting-edge cleanroom environment. Our research aims to develop high-resolution neural probes utilizing state-of-the-art microfabrication techniques.
Keywords
Microfabrication; Cleanroom; Neural Interfaces; Microelectrode Arrays; Biomedical Devices; Nanotechnology; Electrochemical Deposition; Neurotechnology; Semiconductor Processing; Bioengineering.
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Semester Project , Master Thesis
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Published since: 2025-10-13 , Earliest start: 2023-12-01
Organization Bio Engineering Laboratory
Hosts Cardes Fernando
Topics Engineering and Technology
HandoverNarrate: Language-Guided Task-Aware Motion Planning for Handovers with Legged Manipulators
This project addresses the challenge of task-oriented human-robot handovers, where a robot must transfer objects in a manner that directly facilitates the human’s next action. In our prior work, we demonstrated that robots can present objects appropriately for immediate human use by leveraging large language models (LLMs) to reason about task context. However, integrating task-specific physical constraints—such as ensuring a full mug remains upright during transport—into the motion planning process remains unsolved. In this project, we aim to extend our existing motion planning framework for legged manipulators by incorporating such constraints. We propose using LLMs to dynamically generate task-aware constraint formulations based on high-level task descriptions and object states. These constraints will then be used to adjust the cost function of the model predictive controller in real time, enabling more context-sensitive and physically appropriate handovers.
Keywords
language-guided motion planning, legged robotics, human-robot collaboration
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Semester Project , Master Thesis
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Published since: 2025-10-13
Applications limited to ETH Zurich
Organization Robotic Systems Lab
Hosts Tulbure Andreea
Topics Information, Computing and Communication Sciences
Development of a High-Throughput Screening Platform Using Genome Editing, Human Neurons, and High-Density Microelectrode Array Recordings
Genetic screens have been used to probe how autism spectrum disorder (ASD)–associated mutations affect neurogenesis and differentiation. Yet, despite substantial effort, it remains difficult to disentangle cell-autonomous from network-level dysfunctions, and to relate their interplay to ASD’s diverse clinical phenotypes. This project aims to develop a multi-modal, high-throughput loss-of-function screening platform to study ASD-related mutations in human neurons. The methodology will enable perturbation screens and the analysis of how induced genetic alterations shape single-neuron and network-level electrophysiological features. To assess cell-type–specific perturbation effects in excitatory and inhibitory neurons, we will apply transcription-factor (TF)-based forward programming of human induced pluripotent stem cells (iPSCs) combined with combinatorial morphogen treatments. High-density microelectrode array (HD-MEA) recordings coupled to immunohistochemistry and single-cell gene expression analysis will provide an integrated view of how gene knock-outs influence neuronal development and function.
Keywords
Human induced pluripotent stem cells, CRISPR/Cas9 genome editing, neuronal networks, high-density microelectrode array electrophysiology
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Semester Project , Master Thesis
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Published since: 2025-10-10 , Earliest start: 2025-11-01 , Latest end: 2026-09-30
Organization Bio Engineering Laboratory
Hosts Schröter Manuel
Topics Medical and Health Sciences
Student internship - Engineering the Microstructure of Bacterial Cellulose for Sustainable Applications
Biological systems offer routes to build matter with controlled structure and function across scales. Among them, bacterial cellulose (BC) is uniquely attractive: produced as a fibrillar network with high purity and robust mechanical properties, it finds applications in diverse sectors including cosmetics, energy devices, and the biomedical industry. However, most research has targeted BC production yield and cost, while its microstructure, specifically fiber alignment, remains poorly understood and largely engineered post-production.
Keywords
Sustainability - Hydrogel - Mechanical testing - Microscopy
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Semester Project , Internship , Bachelor Thesis , Master Thesis , Master Project (D-MATL)
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Published since: 2025-10-07 , Earliest start: 2026-02-16 , Latest end: 2026-07-01
Organization Complex Materials
Hosts Ansart Elise
Topics Engineering and Technology
How Mechanical Forces Shape Cell Fate – and the Future of Regenerative Medicine
Project Summary We’re developing a powerful new in vitro model to untangle the complex mechanical cues—osmotic pressure and substrate stiffness—that skin cells experience every day. These signals are deeply intertwined in the body, but we’re building a system to decouple and precisely control them, for the first time. Why? Because understanding how cells respond to these forces is crucial for engineering functional tissues, guiding organ regeneration, and tackling mechanobiology-driven diseases like fibrosis.
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Key words: mechanical stresses, cell behavior, fibroblasts, immunostaining.
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Master Thesis
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Published since: 2025-10-07 , Earliest start: 2026-02-01 , Latest end: 2026-10-01
Organization Macromolecular Engineering Laboratory
Hosts Cuni Filippo
Topics Medical and Health Sciences , Engineering and Technology , Biology