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degree in the above mentioned or related fields. What we offer State of the art on-site high performance/GPU compute facilities A team of 30+ expert colleagues A family friendly, green campus with on-site
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complete) an M.Sc. (or equivalent) in Computer Science or a related discipline ML expertise: You have strong programming and deep learning experience (e.g., PyTorch, TensorFlow), backed by a substantial
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and high flexibility in where and when you work. Access to HPC resources (including GPU clusters) at Helmholtz, the Leibniz Supercomputing Centre (LRZ), and the Forschungszentrum Jülich (FZJ). Training
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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work
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on materials science tasks as well as integrate your semantic-AI services into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation Collaborate with
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description With around 6.500 employees and
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, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs) to improve power efficiency and preserve power integrity. Integrated voltage regulators (IVRs
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the EU Research Framework Programme? Other EU programme Reference Number TRB/2025/00026 – ESA-POGS - QKD Is the Job related to staff position within a Research Infrastructure? No Offer Description Note
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We