16 postdoc-computational-fluid-dynamics PhD positions at Linköping University in Sweden
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application! We are looking for a PhD student in Computer Science formally based at the Department of Computer and Information Science (IDA) as part of the national research program WASP. Wallenberg AI
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application! We are looking for a PhD student in Wireless Communication and Computer Vision. Your work assignments Point clouds (PCs) are sets of three-dimensional (3D) data points and their attributes
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7 Mar 2025 Job Information Organisation/Company Linköping University Research Field Computer science » Other Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country
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to meter-sized reactors and relatively slow gas flow velocities. Different modeling methods are necessary to cover all aspects of the CVD process. For instance, a combination of computational fluid dynamics
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and computational methods within quantum mechanics and statistical physics with the aim to design alloys for rare-earth-free high-performance permanent magnets. You will use computational techniques
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part of the national research program WASP. Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for
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multiagent dynamics, with special focus on human decisions and opinion dynamics. The research will deal with both theoretical and computational aspects. The student will develop dynamical models and apply them
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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of the dynamics of macro and micropollutants in AD plants mainly refers to change of bulk properties. The proposed research aims to advance this science to knowledge of transformation processes at the molecular
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of cardiovascular diseases. You will work independently to develop mechanistic models that describe dynamic processes of the microcirculation and analyze large data sets using statistics and deep learning