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We invite applications for a postdoctoral researcher to join the UMLFF project at the University of Luxembourg. The project aims to develop the next generation of uncertainty-aware machine-learning
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Postdoc in Generative Machine Learning for Biomedical Data | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 21.02.2026 Join a place where
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
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developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
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conferences. support the teaching activities at the faculty (up to 10% of the time). What we ask of you A PhD in Machine Learning, Computer Science, Mathematics, Statistics, Physics or a closely related field
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phenomenology, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B