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16 Jul 2026 Job Information Organisation/Company Helmholtz-Zentrum Berlin für Materialien und Energie Research Field Physics Researcher Profile First Stage Researcher (R1) Application Deadline 15
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machine learning, medical imaging, and security venues and journals. Your profile Master's degree in computer science, physics, electrical engineering, mathematics, or a related quantitative discipline
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of shared worlds of imagination that provide orientation and support in everyday life. The process of imagination itself — its practices, dynamics, and historical developments — is at the centre of our
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
, math, physics, or environmental science A background in sea ice and remote sensing Proficient in Python programming Very good English knowledge (approximately equivalent to CEFR level C1) Further
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are looking for a dynamic, serious, and motivated researcher with a Master degree in Geoecology, Geochemistry, Environmental/Organic Chemistry, Geoscience, Physical Geography, Landscape Ecology, Environmental
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of EU to enter the EU countries. Candidates may apply prior to obtaining their master’s degree, but cannot receive an employment contract before having obtained the master’s degree. Selection process
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 2 months ago
stages of the research process, including: designing and implementing experimental studies performing in vivo experiments using mouse models analysing and interpreting complex datasets presenting research
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to the application documents. We kindly ask you to send us only copies (no portfolios) of your application documents, as we cannot return them. They will be destroyed after the selection process has been completed
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cannot return them. They will be destroyed after the selection process has been completed. Data Protection Notice In accordance with §§ 12, 13 GDPR, your application documents will be stored in compliance
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learned representations to guide data acquisition under cost and uncertainty constraints. Building surrogate models that connect imaging-derived representations with downstream physical or functional