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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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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
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able to understand better how and why toxic oligomers form. We are also interested in using our technologies to study enzymes, which are nature's catalytic machines. Enzymes are very important for