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- l'institut du thorax, INSERM, CNRS, Nantes Université
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. Knowledge and Professional Experience: DFT-based methods. Scientific programming in Fortran, in MPI/OpenMP-parallelised codes. Knowledge of other languages (in particular python) and of GPU offloading will be
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simulation frameworks or HPC/GPU-accelerated ML. Proficiency in scientific software development (Python/ML stack, MATLAB for wireless simulation, reproducible workflows, version control). Strong publication
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conducted in collaboration with NVIDIA, leveraging state-of-the-art GPU-based simulation environments and AI platforms. The position will be hosted within the Medical Imaging and Robotics group led by Dr
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exposing hardware accelerators, such as GPUs and FPGAs, in a seamless and portable way. This includes designing execution logic and resource-scheduling strategies that make efficient use of available
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typically work with datasets of up to several TBs depending on the case study); - Autonomy to conduct independent analysis and research on our (GPU/CPU) servers, familiarity with coding frames in machine
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l'institut du thorax, INSERM, CNRS, Nantes Université | Nantes, Pays de la Loire | France | 19 days ago
Devices" ). • Bring various improvements on the synthetic model (vasculature shape / aneurysm / background noise modelling) • Numerical simulations will be performed on a GPU HPC cluster. • Programming in
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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tracking), dataset curation, HPC/GPU programming, blockchain for secure data, C-family languages, and embodied AI/robotics are a plus. Experience with general network resilience, cellular automata
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. Experience with graph-based data analysis or anomaly detection methods. Exposure to high-performance or GPU-based computing environments. Demonstrated ability to contribute to publications or technical reports