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Field
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(PPFE) group at Chalmers conducts research on the modelling, simulation and analysis of magnetically confined fusion plasmas, with a particular focus on tokamak physics. A major part of the research is
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on understanding mechanisms underlying cardiovascular disease, particularly in the context of inflammation, infection and vascular pathology, and on developing advanced experimental models to investigate
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provide complementary expertise. Applicants should identify the profile that best matches their experience; candidates with strengths spanning both areas are also welcome. Profile 1: Model-based radio
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, traffic, infrastructure, behavioural or simulation data in accordance with research-ethics and data-management requirements. Develop, implement, compare and validate quantitative models, which may include
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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to the development of state-of-the-art nuclear-reaction models and evaluated nuclear-data libraries, supporting safe, reliable, and competitive technologies for both existing and future nuclear-energy systems, as
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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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-safety analysis. The research will combine empirical crash and traffic data with statistical modelling, machine learning and traffic or driving simulation to study crash occurrence, injury severity and
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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 12th January 2026
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the link between mechanics and biology in the musculoskeletal system, including related pathologies and repair of skeletal tissues. Experimental studies, tissue characterisation and computational simulation