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, including custom shader development (e.g., CG, GLSL) and adaptation across different graphics backends Experience with performance engineering for mobile, AR, or MR platforms, including GPU/CPU profiling
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, conducting experiments on GPU servers, analyzing results, and maintaining reproducible research pipelines. The candidate will routinely review recent literature, participate in weekly research meetings, and
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experimentation. Familiarity with distributed or accelerated computing environments (e.g., GPU-enabled systems, shared compute clusters ). Working knowledge of database systems, including: Relational databases (e.g
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computing, or hardware reliability. Experience with GPU, FPGA, embedded, or specialized AI accelerator platforms. Experience with scientific programming, benchmarking, or reproducible experimentation
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-dessous. La plateforme ExaNBody [1] développée au CEA est dédiée à la mise en place de simulation à N-Corps dans un contexte de Calcul Haute Performance (CPU/GPU). Elle est notamment utilisée par le
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<span lang="en">Universitätsklinikum Hamburg-Eppendorf</span> | Hamburg, Hamburg | Germany | 8 days ago
resources for travel and conferences
- Work on cutting-edge AI methods with direct clinical relevance
- Access to large-scale multimodal biomedical datasets and modern GPU infrastructure
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, containerisation, version control and service deployment on HPC systems or cloud infrastructure, including GPU-accelerated workloads Experience with deep learning frameworks, production model serving
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Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen | Denmark | about 1 month ago
collaborators. We believe that cooperation and collegiality are essential elements for research successes. You can find more information about the team and our work here: https://www.bric.ku.dk/research-groups
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stimulating working conditions in dynamic and international research environment. Our research facilities include modern laboratories and high-performance computing infrastructure with GPU clusters for
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distributed or accelerated computing environments (e.g., GPU‑enabled systems, shared compute clusters ). Working knowledge of database systems, including: Relational databases (e.g., PostgreSQL / SQL