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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made. The candidate should hold a PhD in experimental physics or similar degree and have
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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. Requirements PhD degree in biochemistry or structural biology, or an exam which is judged comparable to a Swedish Ph.D in biochemistry or structural biology. The degree needs to be obtained by the time of
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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/assignment relevant to the subject area. Candidates who have worked in the lab of the main PI or Co-PI during their PhD and postdoc are not eligible. Step 1: Application The application should include: A