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haute performance (GPU, clusters) appréciées. Qualités personnelles : • Intérêt pour les problématiques interdisciplinaires et volonté d'interagir avec des biologistes et des spécialistes de l'imagerie
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technological platforms on site. The PhD student's work will be carried out at the IGBMC's integrative biology center. He/she will have privileged access to the team's computing server (GPU node) and the
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possible. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. We don’t believe in “one-size-fits-all
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and work together to train models, architect systems, and run trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster
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GPU-accelerated codes. A strong publication record in top-tier journals and conferences. Excellent communication skills and a desire to work collaboratively in a team-oriented research environment
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numerical solvers for 2D and 3D phase field models Develop HPC-ready simulation pipelines for large-scale rupture and fracture-fluid systems Optimize performance for modern architectures including GPUs and
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reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing Knowledge
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. Innovative visualization tools and highly automated analytical pipelines powered by GPU technology. Mentorship from experienced scientists in data analysis and management, with an expertise in delivering high
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GPU clusters and high-performance computing facilities to accelerate your research. Good transport links in a central location with a free job ticket as a contribution to climate protection Low-cost
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will have access to extensive computing resources, including access to ~100 Nvidia H200 GPUs. Applicants should hold a Ph.D. in computer science-related or biomedical research fields relevant