Sort by
Refine Your Search
-
buildings, within a cross-disciplinary environment spanning architectural design, digital technologies and biomaterials science. PhD project summary The PhD student will join our cross-disciplinary research
-
We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
-
Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
-
division at the department of Electrical engineering at Chalmers. Here, a team of PhD students, post-docs and senior researchers are working on modeling and numerical optimization of problems in the areas
-
chemistry and food technology to molecular and data- driven nutrition (Precision Nutrition). In Food Science, we focus primarily on marine and plant-based food systems for which we develop tools and processes
-
PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
-
urban planning. Research environment This PhD position is part of the Sustainable Urban Water and Environmental Engineering (SUWEE) research area within the Department of Architecture and Civil
-
Exciting Opportunity in Sustainable Energy Research: Join Us in Advancing Hydrogen Storage Technology! Hydrogen is a critical energy carrier for future sustainable systems. One issue using hydrogen
-
Are you passionate about railways, acoustics, and data-driven infrastructure solutions? We are looking for a PhD student to join the project “A robust tool for rail fault and roughness estimation
-
Effective use of AI and AI agents requires high quality data. This research is concerned with studying what data companies should collect, how they should process it, where to store it and how