15 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" uni jobs in Germany
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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | 1 day ago
17 Jan 2026 Job Information Organisation/Company EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites Research Field Computer science Environmental science Physics
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Other Positions Application Deadline 31 Mar 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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2038 - 03:14 (UTC) Country Germany 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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tasks: You will work together with renowned astrophysicists and computer scientists in the DFG-funded “Dynaverse” Excellence Cluster You will invent, implement, and benchmark novel AI tools (reinforcement
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
university Basic understanding of remote sensing and Earth observation data Familiarity with Python or R and interest in working with cloud-computing environments Ability to work independently, with attention
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2 Dec 2025 Job Information Organisation/Company Technical University of Munich Research Field Computer science Researcher Profile Recognised Researcher (R2) Country Germany Application Deadline 31
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related to earth sciences for a master’s programme in Germany starting in 2024 (subject to programme resources). Who can apply? Applicants: have successfully completed generally a bachelor’s* degree/a
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2025.11.20.688607; doi: https://doi.org/10.1101/2025.11.20.688607 Moore, J., Basurto-Lozada, D., Besson, S. et al. OME-Zarr: a cloud-optimized bioimaging file format with international community support. Histochem
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on high performance computing systems or cloud infrastructure (including GPU-accelerated workloads). Practical experience with modern deep learning frameworks, model serving in production, and building end
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performance computing systems or cloud infrastructure (including GPU-accelerated workloads). Practical experience with modern deep learning frameworks, model serving in production, and building end-to-end data