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Field
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and trustworthy machine learning-based clinical prediction models. Funded by the Medical Research Council (MRC) and the National Institute for Health and Care Research (NIHR), the project aims
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Potsdam, Brandenburg | Germany | about 13 hours ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:PostDoc in
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funded through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The arrival of large galaxy surveys
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). - Scientific computing experience (e.g., Python, Julia, C, C++). Preferred Qualifications: - Experience with optimization modeling and mathematical programming languages (e.g., GAMS, Pyomo, JuMP). - Experience
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into their models; or 2.Computational social scientists with experience in empirical research and/or theoretical modeling, who are motivated to incorporate their methods into energy modeling. All applicants must
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Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Horizon 2020 Is the
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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Type Staff Job Description Major/Essential Duties of Job: 1. Develop machine learning or physical based models for plant water stress quantification. 2. Develop machine learning models for crop mapping
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sheet modelling demonstrated through a record of publications in scientific journals. Excellent programming skills (e.g. Python, MATLAB, Fortran) and ideally also experience in High-Performance Computing
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biostatistics, - At least 2 years of postdoctoral experience, and if possible experience in supervision (master or PhD students), - Solid background in mathematical modelling and computer programming