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status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status
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or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex
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50 Faculty of Life Sciences Startdate: 01.10.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 17.11.2025 Reference no.: 4674 Explore and teach
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, physical therapy, speech, language and hearing sciences, health science, human physiology, behavior and health, and nutrition. Applicants may learn more about professional development opportunities, benefits
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: High Energy Physics / accelerator , astrophysics , BSM , CMS , cosmology , Dark Matter , Experiment , Flavor Physics , Higgs physics , Lattice QCD , LHC , Machine Learning , Neutrino , Neutrino physics
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relevant to the project's theme and activities. Solid experience in molecular simulation and/or machine learning is required, along with a good knowledge of associated theoretical tools (experience in
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, or a related technical field. ● Strong programming skills in Python, Java, etc. ● Expertise in machine learning, neural networks, and deep learning ● Excellent writing and communication skills ● Highly
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Leonardo. The successful candidate will play a crucial role in developing and optimizing machine learning workflows for large-scale environmental data analysis, contributing to the creation of robust and
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computational tools for analyzing immunogenomics data in the context of gastrointestinal autoimmune diseases and Type 1 Diabetes. Lead the application of AI and machine learning to identify novel therapeutic
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machine learning and statistics; experience with Gaussian process regression and/or probabilistic regression. Experience with normative modelling is an advantage. Proficiency in Python (and ideally C/C