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nearby highways, an indoor SDR testbed for research on next generation wireless communications and sensing, and a GPU Lab for training of advanced machine learning models. IDLab is both part of
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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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l'institut du thorax, INSERM, CNRS, Nantes Université | Nantes, Pays de la Loire | France | about 1 month 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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suitable for part-time employment. Starting date: 17.10.2025 Job description: Design, develop and apply an flexible and integrative multiscale FWI using GPU-accelerated spectral-element simulations (Salvus
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TensorFlow, PyTorch, etc.) Experience with GPU computing, especially for AI/ML calculations Understanding of multi-user computing systems, environments and networks Experience with teaching and/or tutoring in
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resources, including 200+ NVIDIA A100 GPUs and group workstations. Image quality will be assessed using quantitative metrics and clinical expert qualitative review. Privacy safeguards will be built
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, versioned RESTful API (e.g., FastAPI/Flask) for inference; and Containerise services (Docker), set up CI/CD pipelines, and deploy for inference on GPU/CPU servers. Data engineering, Governance, and
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transformations at such interfaces, and how they are influenced by external electric fields and electrolyte composition. Access to high performance computing facilities including GPU clusters will be provided
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deformation, wave propagation, etc. Familiarity with containers, numeric libraries, modular software design. Experience doing performance analysis and tuning. Excellent C/C++ and Python programming skills. GPU
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systems, they increasingly reach their thermal limits due to rapidly rising power densities in modern CPUs and GPUs. Liquid cooling technologies, such as Direct-to-Chip (D2C) can dissipate higher heat loads