302 machine-learning "https:" "https:" "https:" "https:" "https:" "The Francis Crick Institute" research jobs in Germany
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- TH Köln - University of Applied Sciences
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- University of Jena - Cluster of Excellence "Balance of the Microverse"
- University of Oldenburg
- University of Potsdam, Faculty of Science
- Universitätsklinikum Hamburg-Eppendorf
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under: https://jobportal.uni-koeln.de . The reference number is Wiss2602-13. The application deadline is 01.05.2026. For further inquiries, please contact Professor Dr Stefanie Walch-Gassner (walch@ph1
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Muehlleitner (ITP), Prof. Dr. Thomas Schwetz-Mangold (IAP), and Prof. Dr. Felix Kahlhoefer (TTP). KIT is also home to a lively experimental program in astroparticle physics (https://www.iap.kit.edu/english
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workflows within SolMates development of scalable, cloud-based workflows, including the integration of machine learning components into Temporal-based workflow orchestration for data processing, analysis, and
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 8 days ago
given preference. Learn more about diversity at Helmholtz Munich Our commitment Helmholtz Munich Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH) Institute of Biological and Medical Imaging
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | 9 days ago
that provides equal opportunities. We are convinced that diverse teams and a variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection, we aim
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processes, in order to explain their long-term developments and to understand how they resonate into the present (https://www.uni-kiel.de/en/cluster-roots ). ROOTS combines expertise from a wide array of
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Research FieldEngineering » Materials engineeringEducation LevelPhD or equivalent Skills/Qualifications To acquire further scientific qualification (habilitation), the job holder should be able to cover a
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for biotechnology. By combining mecha-nistic, statistical, and machine-learning models with automated experimental execution, the project will enable traceable, reproducible, and metadata-rich experimental planning
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socio-economic analysis, equipping them with advanced skills in reservoir modelling, machine learning, advanced oxidation processes, and microbial enhanced recovery. Candidates will also develop intuitive
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, artificial intelligence (AI), and socio-economic analysis. This program will equip them with advanced expertise in reservoir modelling, machine learning, advanced oxidation processes (AOP), and microbial