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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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Deadline 19 Jan 2038 - 03:14 (UTC) 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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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA
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, parallel processing and hardware-oriented applications and optimisations as well as operating systems. The project will be carried out in close cooperation with Audi in Ingolstadt and Neckarsulm, aiming
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, reproducible computational workflows for large-scale screening and multiscale model integration. HPC at Scale: Run, optimize, and profile large simulations on HPC systems; ensure efficient parallel performance
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structured program. The projects address the three “One Health” aspects: 1) human roundworm infections (close cooperation and fieldwork in Kenya/Africa), 2) roundworm infections in farm animals (chickens and
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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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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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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and/or Matlab, parallel programming Experience in international collaboration Fluent in English (spoken and written) Demonstrated ability to publish in international journals and present at conferences