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build reliable, reproducible data flows for large EO datasets and workflows Lead performance engineering (parallelization, optimization, benchmarking) for adaptation and inference at scale Work closely
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for large EO datasets and workflows Lead performance engineering (parallelization, optimization, benchmarking) for adaptation and inference at scale Work closely with industry partners and public agencies
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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process, the role of ISOs passing through molecular clouds, taking part in molecular cloud collapse and disc formation. Your tasks in detail: Perform scientific work on the research topic, in collaboration
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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc. You will be involved in all phases of this process. You will