35 computer-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Institute-for-Advanced-Study" Fellowship positions in Germany
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Max Planck Institute for the History of Science, Berlin | Berlin, Berlin | Germany | about 18 hours ago
Job Offer from October 01, 2026 First Research Article Fellowship Program at the Max Planck Institute for the History of Science, Berlin 01 September 2027 – 28 February 2028 The Max Planck
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(100%, E 13 TV-L, 3 years + possible extension, m/f/d) We seek a highly-motivated postdoctoral research fellow with strong expertise in cognitive computational modeling and an interest in applying
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available in the further tabs (e.g. “Application requirements”). Programme Description Copernicus Hamburg awards fellowships to Eastern and Central European, North African and Central Asian students every
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available in the further tabs (e.g. “Application requirements”). Objective 'DLR-DAAD Research Fellowships' is a programme implemented by the 'German Aerospace Center' (DLR) and the 'German Academic Exchange
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available in the further tabs (e.g. “Application requirements”). Objective The primary aim of this programme is to promote the research projects within the context of the doctoral degrees and scientific
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Cybernetics (https://www.kyb.tuebingen.mpg.de/en ) is a world-renowned research hub for computational modeling and cognitive neuroscience. This unique research environment provides the postdoctoral researcher
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available in the further tabs (e.g. “Application requirements”). Programme Description The international Leo Baeck Fellowship Programme awards grants to doctoral students who carry out research
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outstanding international postdoctoral researchers to Heilbronn's rapidly growing AI ecosystem. The programme supports cutting-edge AI research at institutions on the Bildungscampus Heilbronn and across
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of molecular data. While machine learning has transformed fields such as computer vision and natural language processing, the molecular life sciences remain a rich frontier for methodological innovation
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fields such as computer vision and natural language processing, graph-structured data remain a rich frontier for methodological innovation, with many fundamental challenges and exciting opportunities ahead