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) • An occupational health management model with numerous attractive options, such as our university sports programme • Supplementary pension scheme (RZVK) • Discounted tickets on local public transport services (‘Job
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(TIB ) – Leibniz Information Centre for Science and Technology – Program Area D, Open Research Knowledge Graph, is looking to employ a Research Software Engineer for “Physics Ask” (m/f/d) to work in Team
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 20 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
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experiments in in-house labs and at user facilities data analysis, modelling and interpretation, also in collaboration with scientific partners extensive literature research dissemination of scientific results
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specialists Requirements: Degree in Medical Informatics, Data Science, Statistics, Computer Science, or related field Experience in SQL, data modeling, and statistical analysis Proficiency in Python and/or R
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The planetary geodynamics group led by Prof. Dr. Lena Noack uses computational models to characterize planetary processes that impact the long-term evolution of the planetary interior coupled
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Deadline 5 Nov 2025 - 23:00 (UTC) Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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image analysis to establish objective, fast, and scalable testing methods for the textile and cosmetics industries. Your tasks Development and implementation of AI/ML models (Deep Learning, Computer
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For a behavioral experimental economics project on ‘Mental Models and Discrimination’ (leadby Kai Barron, PhD) in the Research Department ‘Market Behaviour’ within the Research Area ‘Markets and
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foundation and practical experience in machine learning and reinforcement learning Experience in training and evaluation of machine learning models on large high performance computing infrastructure Existing