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Minimal is a mostly 3D-printed, highly reconfigurable robot. Using state-of-the-art reinforcement learning, we will explore novel and highly advanced hardware design possibilities that will be coupled with design optimization through learning. This will enable the next generation of robots to be a lot faster, stronger and agile. - Engineering and Technology
- Master Thesis, Semester Project
| The aim of this project is to implement and test different T1ρ measurement approaches using MR simulations and measurements. - Biomedical Engineering, Medical Physics
- Bachelor Thesis, Semester Project
| 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 decision transformers, trained on offline data, to accomplish these tasks. - Intelligent Robotics
- Master Thesis, Semester Project
| The accumulation of metals in tissues can either contribute to or arise from metabolic disorders, resulting in supraphysiological concentrations of deleterious species within organs and tissues. Chronic metal overload can lead to organ failure and arthritis, while in the short term is proinflammatory and complicates wound healing. - Biomaterials, Chemical Engineering, Chemistry
- Bachelor Thesis
| The traveling velocity of Swiss pendolino reaching 250 km/h creates both aerodynamic noise
as well as noise from the train wheel – track interaction. Corrundum grinding wheels are
widely used in industry for maintaining rail tracks and acoustic grinding. Rolling noise
contributes significantly to the overall acoustic pollution, whereby correlation between track
surface quality and noise emission could be detected and needs to be improved.
It is a challenge to measure the rail roughness from the train, to monitor the condition of the
rail network at a high speed. For this purpose, an optical measurement system is to be developed which can measure the
rail roughness contact-free. A possible additional topic is the detection of rail defects using
machine learning. From design to performing experiments to data processing or data storage
strategies, a variety of thesis topics are possible. - Mechanical Engineering
- Bachelor Thesis, Semester Project
| Our lab is looking for a highly motivated Master student (6-12 months), who is interested to conduct a research in the field of disease modeling using ADHD patient-specific cells. The process will involve learning how to analyze preexisting data from single cell RNA sequencing (scRNAseq) generated from neural stem cells (NSCs) and forebrain cortical neurons (FCNs) derived from human induced pluripotent stem cells (iPSCs), by using bioinformatics. These cell lines were previously generated in our lab and are derived from patients with Attention-Deficit Hyperactivity Disorder (ADHD). We will investigate the transcriptome profile of both NSCs and FCNs, which will include analyzing the Wnt signaling pathway. This pathway plays a crucial role in coordinating important cellular events during neurodevelopment. Moreover, the student will learn how to scientifically interpret and discuss scientific papers and conduct research with independence and critical thinking. - Cell Development (incl. Cell Division and Apoptosis), Computational Biology and Bioinformatics, Neurosciences, Psychiatry, Quantitative Genetics
- Master Thesis
| The project focuses on optimizing the compact Marx generator, which charges capacitors in parallel and discharges in series to produce high-voltage pulses. Through FEM simulations, the objective is to design capacitor arrangements that limit the electrical field, mitigating equipment failures, and extracting parasitic elements. - Electrical Engineering
- Semester Project
| In this project, you will investigate how to design appropriate geometries for spark gaps and extract the electrical parasitic elements. You will create a parametrized simulation linking Matlab and COMSOL to optimize the parasitic elements. - Electrical Engineering
- Master Thesis, Semester Project
| Searching for specific objects within a confined space requires advanced spatial and perceptual reasoning. In this project, we want to develop a learning-based system that finds a desired object in a cluttered scene efficiently and safely. - Computer Vision, Knowledge Representation and Machine Learning, Learning, Memory, Cognition and Language
- Master Thesis
| This project is part of a collaboration between the IMOS lab and Matterhorn Gotthard Bahn, a railway company operating in the Swiss Alps. The student will work on developing computer vision algorithms for automated visual inspection of retaining walls around railway tracks. Retaining (or supporting) walls are crucial infrastructure elements responsible for maintaining the structural integrity of terrains around railway tracks and ensure safe operation. They are subject to wear and damages including cracks, concrete cancer (i.e., alkali–silica reaction), displacements, erosion and water infiltration. Images of retaining walls have already been collected and labels are available. The goal will be to design algorithms to estimate the condition of a wall, with a focus on robustness, transfer learning, and explainability (XAI). - Engineering and Technology, Information, Computing and Communication Sciences
- Internship, Master Thesis, Semester Project
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