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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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focus on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid
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numerical models and signal processing methods to detect and understand seismic events directly from communication signals in optical fibers — paving the way for a new class of communication-based seismic
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on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid state
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agreement. Starting date: January 2026. Job description: The postdoc project is focused on analysis or numerical methods for non-linear partial differential equations. The target applications include
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to the development of methodologies for modelling, predicting, and validating dynamic interactions through numerical simulations and field measurements. This project is funded by The Swedish Transport Administration
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collaborate on modelling and numerical optimization in robotics, electromobility, and autonomous driving. The team is international and combines expertise in control, optimization, and statistical inference. A
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. About us You will join the Systems and Control division at the Department of Electrical Engineering , where PhD students, postdocs, and senior researchers collaborate on modelling and numerical
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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different mixing and reactive properties compared to conventional fuels. In this project, turbulent mixing and combustion of hydrogen in air will be studied through optical experiments and numerical modelling