University of Zurich

Open Opportunities

Comparing Human and Meta-RL Learning Strategies Using Cognitive Latents University of Zurich Christian Ruff This thesis aims to bridge the gap between human decision-making under uncertainty and artificial intelligence. Building upon recent neuroimaging research from our group on how the human brain processes probability and uncertainty of motivational events, this project will investigate whether meta-reinforcement learning (meta-RL) models can accurately replicate these complex neural computations and match human performance on a specific Pavlovian task. Ultimately, the goal is to understand the similarities and differences in how AI and biological intelligence handle learning and decision-making in uncertain environments. Computer Perception, Memory and Attention, Neurocognitive Patterns and Neural Networks, Neurosciences, Simulation and Modelling Master Thesis

Investigating cells mechanical properties via Fluidic Force Microscopy in a 2D autoimmune skin disease model ETH Zurich Biosensors and Bioelectronics (LBB) The remarkable complexity of morphogenesis and tissue regeneration implies the existence of a transcellular communication network in which individual cells sense the environment and coordinate their biological activity in time and space. To understand the fascinating ability of tissue self-organization, comprehensive study of biophysical properties (cellular nanomechanics such as tension forces and bioelectromagnetics) in combination with the analysis of biochemical networks (signaling pathways and genetic circuits) is required. In this framework we are investigating the unacknowledged key role of Desmoglein 3 (Dsg3) as a receptor involved in mechanosensing, capable of initiating a signaling response in the transcellular communication network, which results in stem cell fate conversion, plasticity and tissue repair. Our goal is to apply innovative Fluidic Force Microscopy to measure altered biophysical parameters upon disruption of Dsg3 transadhesion such as cell stiffness, cell-cell adhesion, cell surface charges and electric potentials. Together with the University of Bern and University of Lübeck we are further investigating how these biophysical changes relate to transcriptomic, epigenomic and proteomic response circuits to ultimately infer biophysical and biochemical circuits involved in Dsg3 signaling. Biochemistry and Cell Biology, Biomedical Engineering, Medical and Health Sciences, Physics Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project

Agile Flight of Flexible Drones in Confined Spaces University of Zurich Robotics and Perception The project aims to create a controller for an interesting and challenging type of quadrotor, where the rotors are connected via flexible joints. Control Engineering, Flight Control Systems, Intelligent Robotics, Systems Theory and Control Master Thesis, Semester Project

Vision-Based World Models for Real-Time Robot Control University of Zurich Robotics and Perception This project aims to use vision-based world models as a basis for model-based reinforcement learning, aiming to achieve a generalizable approach for drone navigation. Computer Vision, Intelligent Robotics, Simulation and Modelling Master Thesis, Semester Project

Vision-Based Reinforcement Learning in the Real World University of Zurich Robotics and Perception We aim to learn vision-based policies in the real world using state-of-the-art model-based reinforcement learning. Computer Vision, Flight Control Systems, Intelligent Robotics Master Thesis, Semester Project

How does the environment affect economic decisions? University of Zurich Philippe Tobler Do you feel more in the mood to book a ski weekend on a sunny Monday or a rainy Monday? Our decisions can be influenced by many factors—including the environment around us. This study explores how non-social environmental factors, such as current and past weather and temperature, influence economic decision-making, including risk-taking, choice consistency, and rationality. We aim to develop a data analysis pipeline for processing large datasets with multiple features, using machine learning techniques like lasso and ridge regression to identify key predictors of economic behavior. The project involves parameter tuning, assumption checking, and feature selection to ensure robust, interpretable models. If time permits, weather data will be scraped from the web based on geolocation to further enhance the analysis of environmental conditions. By investigating how these contextual factors shape economic decisions, we aim to provide insights into the dynamic forces influencing individual choices, challenging the view of economic preferences as stable dispositions. Behavioural and Cognitive Sciences, Economics Master Thesis, Semester Project

Ph.D. Position in AI for Good in the Context of News Recommender Systems  University of Zurich Dynamic and Distributed Information Systems The Dynamic and Distributed Information Systems Group at the University of Zurich is looking for motivated applicants who are interested in investigating how news recommender systems can have a more diverse coverage of recommended items from a societal perspective, be fair and transparent, and provide more control to users using modern technologies such as generative AI. Computer-Human Interaction PhD Placement

Ph.D. Position in Generative AI in the Context of News Recommender Systems University of Zurich Dynamic and Distributed Information Systems The Dynamic and Distributed Information Systems Group at the University of Zurich is looking for motivated applicants who are interested in developing personalized news recommender systems using generative AI technology. Computer-Human Interaction PhD Placement

Tissue Engineering Approaches to Study Tendon Injury, Disease, and Therapy ETH Zurich Snedeker Group / Laboratory for Orthopaedic Biomechanics Join a dynamic research team at the intersection of biomechanics, tissue engineering, and cell biology. This project offers hands-on training in state-of-the-art methods to investigate how tendon tissue responds to injury, disease processes, and mechanical stimulation during exercise-based therapy. Biomedical Engineering Master Thesis

Measuring Cell Contractility with Confocal Traction Force Microscopy ETH Zurich Biosensors and Bioelectronics (LBB) In this project, you will explore how cells generate mechanical forces using confocal traction force microscopy (cTFM). The project combines experimental techniques, such as cell culturing, quantum dot array printing, and live-cell confocal imaging, together with computational data analysis using the open-source tool Cellogram. By growing cells on deformable substrates and tracking the displacement of fluorescent quantum dots, students will quantify the traction forces that individual cells exert on their environment. Biology, Engineering and Technology, Information, Computing and Communication Sciences Bachelor Thesis, Master Thesis, Semester Project