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processes, Bayesian inference, signal models, sampling theory, sensing techniques, optimisation theory and algorithms, multi-modal data processing, high-performance computing, mathematical image analysis
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Methodological competence: Strong programming skills, ideally including experience in deep learning and/or high-performance computing Passion for method development Very good English communication skills – both
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within the 2DPHYS and CAMD sections at DTU Physics as well as at DTU Compute and DTU Nanolab. Required qualifications Significant experience with theoretical and computational nanophotonics High level of
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focuses on a theoretical and computational studies of condensed matter physics, with emphasis on the following frontier topics: - Topological quantum matter, non-Abelian anyons and topological quantum