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simulation workload and update the solver data structures when the mesh changes. These approaches would be applied on modern large-scale heterogeneous parallel computing environments where both CPUs and GPUs
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limited to deep learning Experience utilising GPU enabled High-Performance Computing environments is an asset Open minded critical thinker, willing to actively contribute to the further development of multi
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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Your research will be conducted at the Department of Urology, the Department of Pathology and Clinical Bioinformatics at Erasmus MC in Rotterdam, and in collaboration with the Computational
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, large-scale medical datasets and high-performance computing infrastructure (including NVIDIA B300 GPUs) Funding for publications, international conferences, and research mobility grants Support from TUM
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Deadline 16 Jan 2026 - 23:00 (UTC) Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing
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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 1 month ago
Germany Application Deadline 2 Nov 2025 - 22:59 (UTC) Type of Contract To be defined Job Status Other Offer Starting Date 17 Oct 2025 Is the job funded through the EU Research Framework Programme? Not
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in high-performance computing using MPI. Experience in GPU programming using OpenACC, CUDA, CUDA-Fortran, Julia, or related tools. Experience in CFD meshing software. TU Delft (Delft University
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applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience with ML/DL workflows and