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 |
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Tree species maps are crucial for effective forest management, biomass assessment, and biodiversity monitoring. Remote sensing products offer flexible and cost-effective ways to assess forest characteristics, while deep learning methods promise high predictive accuracy and transformative applications in forestry. This study aims to apply novel deep learning approaches to detect and identify individual trees and tree species in mixed forests. By addressing the challenges of tree species identification, this research will enhance biodiversity assessment, forest resilience understanding, and management strategies. - Artificial Intelligence and Signal and Image Processing, Forestry Sciences, Geomatic Engineering
- ETH Zurich (ETHZ), Master Thesis
| 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
| Fracture surfaces in rock cores contain valuable structural information crucial for geological interpretation, engineering design, and are commonly mapped and analyzed by geologists. With advancements in camera technologies and computational techniques, it is now possible to digitize these surfaces in high resolution and apply automated methods for fracture analysis. - Computer Vision, Geology, Image Processing, Photogrammetry and Remote Sensing
- Bachelor Thesis, Master Thesis, Semester Project
| 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
| 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
| 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
| The proliferation of mobile and embedded devices has spurred the demand for efficient, high-quality
speech synthesis systems that operate entirely on-device. This project aims to develop a fast,
quantized speech synthesis pipeline optimized for mobile platforms (i.e. Samsung Galaxy, Google
Pixel Pro 8), focusing on reducing computational load and memory usage without compromising
audio quality. - Engineering and Technology, Information, Computing and Communication Sciences
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| 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
| 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
| Switzerland is committed to achieving net-zero greenhouse gas emissions by 2050. Innovative and sustainable freight solutions are essential as the transport sector accounts for a significant share of CO2 emissions. Currently, road transport dominates the modal split (62%), with rail transport contributing only 38%.
Traditional urban logistics rely heavily on road-based transport, contributing to congestion, emissions, and inefficiencies in last-mile delivery. While rail offers a sustainable alternative for long-distance freight, its integration into city logistics remains limited. Therefore, this thesis investigates how a fully electric railway supply chain centered around a rail-city portal (e.g., intermodal urban connectors between rail and last-mail logistics) can reduce emissions and improve the efficiency of urban freight distribution. A rail-city portal can be a transshipment node, bridging rail and e-mobility for last-mile logistics.
- Transport Economics, Transport Engineering, Transportation
- Master Thesis
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