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2 Sep 2025 Job Information Organisation/Company Technische Informationsbibliothek (TIB) Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions
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Deadline 11 Oct 2025 - 22:00 (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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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | about 2 months ago
of English and German, experience in project management, an affinity for modern technology, and strong communication skills. A university degree (Master or preferably PhD) is required and a scientific
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representations. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing
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medicine in life sciences. Our platform will empower researchers to collaborate across institutions, utilizing cloud and on-premise computing and storage resources to drive scientific innovation
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such as glossaries and bibliographies for the volumes Producing content for the series website Required qualifications and experience: PhD, ideally in history, already awarded, on a relevant topic (National
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(R1) Country Germany Application Deadline 19 Oct 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 5 days ago
Researcher (R4) Country Germany Application Deadline 2 Oct 2025 - 21:59 (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
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Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description “Research for a life without cancer” is our mission at the German
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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