Department of Mechanical and Process EngineeringAcronym | D-MAVT | Homepage | http://www.mavt.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | Department of Mechanical and Process Engineering | Child organizations | |
Open OpportunitiesDespite the growing amount of work on applying causal discovery method with expert knowledge to areas of interest, few of them inspect the uncertainty of expert knowledge (what if the expert goes wrong?). This is highly important since that in scientific fields, causal discovery with expert knowledge should be cautious and an approach taking expert uncertainty into account will be more robust to potential bias induced by individuals. Therefore, we aim to develop an iterative causal discovery method with experts in the loop to enable continual interaction and calibration between experts and data.
Based on the qualifications of the candidates, we can arrange a subsidy/allowance for covering traveling or living costs. - Expert Systems, Health Information Systems (incl. Surveillance), Statistics
- Internship, Master Thesis, Semester Project
| This project focuses on developing an explainable Artificial Intelligence (xAI) framework based on graphical modeling (GM), to enhance the capacity and capability of medical AI. Collaborating with the Swiss Paraplegic Centre (SPZ) for validation, our goal is to improve the long-term prognosis of spinal cord injury (SCI) individuals. Through medical records and a multimodal sensory monitoring system, we aim to create digital twins capable of integrating diverse data sources, guiding medical treatment, and addressing common secondary health conditions in the SCI population. The envisioned GM-based digital twin (GMDT) will represent hierarchical relations across demographic features, functional abilities, daily activities, and health conditions for SCI individuals, allowing for downstream tasks such as prediction, causal inference, and counterfactual reasoning. The assimilation and evolution between the physical and digital twins will be implemented under the GM framework, promising advancements in personalized healthcare strategies and improved outcomes for SCI people. Please refer to the attached document for more details about the task description. Based on the candidate's qualifications, funding/allowance can be provided. - Biomedical Engineering, Digital Systems, Knowledge Representation and Machine Learning, Pattern Recognition, Simulation and Modelling
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| The process of evaluating sleep examinations and diagnosing sleep disorders through polysomnographies (PSGs) is labor-intensive as it requires manual analysis from sleep technicians and doctors. In collaboration with Clinic Barmelweid, a leading sleep and rehabilitation clinic in northwestern Switzerland, we plan to automate this process using machine learning models. Clinic Barmelweid conducts approximately 400-450 PSGs annually and has access to a dataset of more than 5,000 recordings. - Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Medical and Health Sciences
- Collaboration, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| This Master's thesis focuses on the experimental determination of material properties for Ti6Al4V, essential for the numerical simulation of machining processes. The work involves preparing various samples, conducting flow curve tests, damage behavior analyses, and anisotropy assessments. Additionally, EBSD analysis, hardness measurements, and potentially chemical analyses will be performed. The results will be used to validate machining simulations using SPH/FEM, comparing process forces and chip formation. - Mechanical and Industrial Engineering
- ETH Zurich (ETHZ), Master Thesis
| This Master's thesis focuses on the experimental determination of material properties for stainless steel, essential for the numerical simulation of machining processes. The work involves preparing various samples, conducting flow curve tests, damage behavior analyses, and anisotropy assessments. Additionally, EBSD analysis, hardness measurements, and potentially chemical analyses will be performed. The results will be used to validate machining simulations using SPH/FEM, comparing process forces and chip formation. - Mechanical Engineering
- ETH Zurich (ETHZ), Master Thesis
| The goal of the project is to develop and test a smart sock prototype for plantar pressure measurements. The smart sock contains textile based pressure sensors and a readout module. This technology can be used for plantar pressure monitoring in diverse wearable applications ranging from healthcare to sports. - Biomedical Engineering, Medical and Health Sciences
- Master Thesis
| The goal of the project is to assess the feasibility of using commercially available plantar pressure monitoring devices (so called smart insoles) on the diabetic population. Pressure ulcers are a common complication of the diabetic foot, and monitoring plantar pressure continuously is a potential measure of prevention. Diabetic patients are often prescribed personalized footwear (e.g., curved insoles that accommodate any deformity in the feet). This project aims at assessing the potential of the smart insoles available on the market to monitor plantar pressure in diabetic patients with such custom footwear. - Biomedical Engineering, Medical and Health Sciences
- Bachelor Thesis, Semester Project
| This project mainly focuses on the automation of the existing 5D bioprinter, optimizing the software for updated system use, and developing the print head for better complex 3D prints. This printer will be used for bioprinting applications. - Acoustics and Acoustical Devices; Waves, Automotive Engineering, Biomedical Engineering, Computer Hardware, Control Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Printing Technology, Robotics and Mechatronics, Systems Theory and Control
- Bachelor Thesis, Master Thesis, Semester Project
| The Multi-Scale Robotics Lab develops novel actuation methods for endoscopic devices utilizing magnetic navigation systems (MNS). In MNS, an external magnetic field applies forces and torques on magnets attached to the endoscopes. To control these endoscopes, precise shape estimation techniques are required. Current methods try to estimate the endoscope’s shape by measuring the external field along the endoscope using hall-sensors. This method requires precise knowledge about the applied external field and often lacks in localization precision in certain directions.
- Electrical Engineering, Mechanical Engineering
- Master Thesis
| Bühler, a leading industry manufacturer in Uzwil, is partnering with ETH Zürich's Feasibility Lab to offer a unique master thesis opportunity. Throughout your thesis, you'll work hand-in-hand with a team of like-minded peers, following the principles of cross-functional teamwork and agile project planning. You can explore your interests in AI/Machine Learning, Robotics, UX, Additive Manufacturing, Food Science and more and actively define your own project scope. - Digital Systems, Environmental Technologies, Industrial Biotechnology and Food Sciences, Interdisciplinary Engineering, Manufacturing Engineering, Mechanical and Industrial Engineering
- ETH Zurich (ETHZ), Master Thesis, Semester Project
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