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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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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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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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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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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
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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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empower researchers to collaborate across institutions, utilizing cloud and on-premise computing and storage resources to drive scientific innovation. The University Computing Centre (URZ) is the central IT
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relevant experience in the field, ideally with a PhD Background knowledge in cancer genomics Proficiency in Bash scripting and R and experience with cloud computing (required) Proficiency in Python and Git
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systems, software, and cloud services. Novatron employs around 130 professionals, including 60 engineers and scientists in R&D. https://novatron.fi/en/ More about Tampere and Finland: Application Procedure
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programming skills (Python; ideally with experience in databases and cloud environments). Experience in image analysis and computer vision, ideally in the context of biological samples or materials science