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at the Division of Fluid Dynamics, within the Department of Mechanics and Maritime Sciences at Chalmers. The project is carried out in collaboration with Vattenfall Research and Development, and is part of
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related courses. Documented knowledge in kinetic theory, non-local diffusion or dynamics on graphs is beneficial but not a requirement for the position. Good communication skills in both written and spoken
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engineering and maritime sciences: Dynamics, Fluid Dynamics, Vehicle Safety, Vehicle Engineering & Autonomous Systems, Combustion and Propulsion Systems, Marine Technology and Maritime Studies. The seven
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
the position to five years. A dynamic and inspiring working environment in the coastal city of Gothenburg . A starting salary of 34,550 SEK per month (valid from May 25, 2025). Chalmers is dedicated to improving
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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) at AstraZeneca, and Dr. Margaret Holme (Assistant Professor) at Chalmers, within a cross-functional and dynamic research environment. This is a unique opportunity to shape the future of data-driven drug delivery
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that utilize streets and roads to manage stormwater, there is limited knowledge on effective design and implementation strategies. This PhD project aims to investigate how urban roads can be designed and
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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application! We are now looking for a PhD student in Automatic Control, at the Department of Electrical Engineering (ISY). Your work assignments The research area of this position is complex networks and
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flow phenomena. The goal is to integrate theoretical and experimental fluid dynamics with modern computational tools to analyze and predict multiphase flow behavior. The project also involves applying