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The Department of Physics at Chalmers University of Technology invites applications for a postdoc position targeting machine learning in optics. In this position, you will become part of a
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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites
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groups working towards a common goal. For this postdoc project, we seek a dynamic and motivated candidate with an interest in computational electromagnetism, inverse design, and/or machine learning in
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This position offers a unique opportunity to work at the intersection of statistical machine learning, control theory, and transport safety, in collaboration with researchers at Chalmers and the
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intelligence, machine learning, data science, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine
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are looking for The following requirements are mandatory: To qualify for the position of postdoc, you must hold a doctoral degree in computer science, artificial intelligence, machine learning, data science
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for the doctoral degree. Exceptions from the 3-year limit can be made for longer periods resulting from parental leave, sick leave or military service. The following experience will strengthen your application
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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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– from materials design and processing to machining, mainly of metals. Our expertise spans powder metallurgy, electroplating, additive manufacturing, and material removal, combined with advanced
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Optimal Control Theory Strong programming skills in C++/Python/MATLAB Familiarity with parallelization and high performance computing (CPU and GPU friendly code) Experience with Machine Learning, generative