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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We
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available in the further tabs (e.g. “Application requirements”). Programme Description As part of the HessenFonds, the Hessian Ministry of Higher Education, Research, Science and the Arts provides
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(Leibniz Gemeinschaft) and committed to international standards of excellent science. The IWM invites applications for the position of a Post-Doctoral Researcher (m/f/d) Full-time, fixed term for three years
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available in the further tabs (e.g. “Application requirements”). Programme Description The programme is intended for outstanding junior post-doctoral scientists from Germany, Austria and Switzerland from all
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available in the further tabs (e.g. “Application requirements”). Programme Description Applicants holding a PhD or who are eligible to be a junior professor in the historical humanities are invited to apply
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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on the Bildungscampus Heilbronn (Heilbronn Education Campus). TUM Campus Heilbronn focuses on the areas of managing digital transformation, family businesses, and computer science. Requirements - Master’s degree in
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the following areas: PhD in mechanical/electrical engineering, robotics, computer science, or a comparable field, Experience in self-reliant managing of research projects (financial and administrative) and
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mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning