Search for public opportunitiesRegister now and browse all open positions. It's free!Profit from a great search interface and directly apply to the position of your choice. SiROP - Excellence in Science! Profit from a great search interface and directly apply to the position of your choice. SiROP - Excellence in Science! Notify me when new projects of my interest are advertized!You define what you are interested in and we will send you an Email when a new project matches your criteria, it's that easy. You define what you are interested in and we will send you an Email when a new project matches your criteria, it's that easy. Results |
|---|
Agriculture is widely recognized as one of the most vulnerable sectors to the adverse effects of climate change, which is particularly true for arable farming. Projections indicate that these effects will worsen in the coming decades. Farmers will have to adapt to the changing climate. Multiple climate change adaptation strategies have been suggested over the last decades, including, e.g., diversification, conservation tillage or crop insurance. However, little is known about the behavioral factors influencing the adoption of such strategies. This master thesis aims to investigate the influence of farmers’ behavioral characteristics on the uptake of climate change adaptation measures in the context of German arable farming. - Agricultural, Veterinary and Environmental Sciences, Economics
- Master Thesis
| We are developing an acoustofluidic platform that can increase the efficiency of microtissue histology. But most steps in this long process workflow are currently performed manually. To achieve high throughputs, we are interested in developing a 3-axis linear manipulator compatible with the established acoustofluidic-enhanced-histology workflow that automates most of the steps. - Mechanical Engineering, Robotics and Mechatronics
- ETH Zurich (ETHZ), Master Thesis
| These two PASC projects focus on advancing electronic-structure simulations by implementing novel mixed-precision numerical algorithms in the DFTK.jl and SIRIUS libraries, enhancing their integration with Quantum ESPRESSO, and to incorporate advanced electronic-structure functionals based on frequency-dependent response functions (dynamical Hubbard functionals) to improve the accuracy and efficiency of first-principles calculations. - Theoretical and Computational Chemistry, Theoretical and Condensed Matter Physics
- Post-Doc Position
| Agriculture is widely recognized as one of the most vulnerable sectors to the adverse effects of climate change. This thesis aims to identify effects of weather shocks on farm structural indicators. It combines official statistics provided by the EU with meteorological data and provides causal estimates of weather shocks on farm structural indicators using econometric methods. - Agricultural, Veterinary and Environmental Sciences, Economics
- Master Thesis
| Are you passionate about science and sustainability? Conduct your own innovative research at the intersection of chemistry and biotechnology, pioneering the conversion of renewableresources into valuable fine chemicals. - Biology, Chemistry, Engineering and Technology
- PhD Placement
| Für eine laufende Studie suchen wir nach einem motivierten Praktikanten / Masterstudenten, Details im PDF - Biomechanics
- Internship, Master Thesis
| In the BIROMED-Lab we have been developing an endoscopic system for safer neurosurgeries with inspiration from human finger anatomy. Its two degrees of freedom allow the endoscope to investigate areas of the brain that would be inaccessible with standard rigid endoscopes. Thanks to springs in the transmission between the motors and the movable endoscope tip, the interaction forces between the instrument and the brain tissue can be reduced. Furthermore the interaction forces can be estimated by measuring the deflection of the spring. To make the telemanipulation of the endoscope safer and more intuitive for the surgeon, force feedback was also implemented. - Biomedical Engineering
- Master Thesis
| Robotics is dominated by on-policy reinforcement learning: the paradigm of training a robot controller by iteratively interacting with the environment and maximizing some objective. A crucial idea to make this work is the Advantage Function. On each policy update, algorithms typically sum up the gradient log probabilities of all actions taken in the robot simulation. The advantage function increases or decreases the probabilities of these taken actions by comparing their “goodness” versus a baseline. Current advantage estimation methods use a value function to aggregate robot experience and hence decrease variance. This improves sample efficiency at the cost of introducing some bias.
Stably training large language models via reinforcement learning is well-known to be a challenging task. A line of recent work [1, 2] has used Group-Relative Policy Optimization (GRPO) to achieve this feat. In GRPO, a series of answers are generated for each query-answer pair. The advantage is calculated based on a given answer being better than the average answer to the query. In this formulation, no value function is required.
Can we adapt GRPO towards robot learning? Value Functions are known to cause issues in training stability [3] and a result in biased advantage estimates [4]. We are in the age of GPU-accelerated RL [5], training policies by simulating thousands of robot instances simultaneously. This makes a new monte-carlo (MC) approach towards RL timely, feasible and appealing. In this project, the student will be tasked to investigate the limitations of value-function based advantage estimation. Using GRPO as a starting point, the student will then develop MC-based algorithms that use the GPU’s parallel simulation capabilities for stable RL training for unbiased variance reduction while maintaining a competitive wall-clock time.
- Intelligent Robotics, Knowledge Representation and Machine Learning, Robotics and Mechatronics
- Bachelor Thesis, Master Thesis, Semester Project
| Are you passionate about microbiology, molecular biology, or environmental science? Join us in exploring the unseen microbial world through two exciting research projects! - Computational Biology and Bioinformatics, Ecology and Evolution, Geology, Microbiology
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| This project explores a novel approach to graph embeddings using electrical flow computations. - Artificial Intelligence and Signal and Image Processing, Knowledge Representation and Machine Learning, Mathematics
- Master Thesis
|
|
