24 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at University of Tübingen in Germany
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11.12.2025 Application deadline: 15.02.2026 The Faculty of Science at Tübingen University invites applications for a W3-Professorship in Machine Learning in Physics at the Department of Physics (m/f
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Mainmenu Information for Prospective Students Current Students Staff Teaching Staff Alumni Media Business Lifelong learning Quicklinks All Degree Programs ALMA Portal Excellence Strategy Staff Search (EPV
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from equally qualified candidates with disabilities will be given preference. General information on professorships, hiring processes, and the German academic system can be found here: https://uni
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@ifu.uni-tuebingen.de by February 28th, 2026. Further information on the Cluster of Excellence can be found here: https://uni-tuebingen.de/en/research/core-research/cluster-of-excellence-human-origins
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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programme, please see https://uni-tuebingen.de/en/faculties/faculty-of-science/doctoral-studies/ and https://www.phd.tuebingen.mpg.de/imprs? Assessment Submitted applications will be reviewed by IMPRS
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute