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Field
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to
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include: Assist in porting quantum computing optimization codes to CUDA-Q for use with NVIDIA GPUs. Collaborate with NLR researchers on developing formulations and algorithms for solving optimization under
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following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing (HPC
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and have prior experience with remote GPU and HPC services. After the qualification requirements, great emphasis will be placed on personal skills. Target degree: Doctoral degree Information regarding
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good understanding of the physics of scattering and antenna radiation Programming experience in C/C++ is necessary while experience in parallel and GPU computing is most desired More Information Location
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
laptop equipped with a GPU and funding to participate in summer schools and national and international conferences. The thesis work will also be supervised by a CNES research engineer as part of
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megawatts. To transfer energy efficiently from the grid to CPUs/GPUs, higher system voltages are required in data centres/computer racks, and efficient power electronics converter systems based on SSTs
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RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent written and oral communication skills. Motivated self-starter with
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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regulation to neuronal function and circuits. State-of-the-Art Infrastructure: Access to advanced sequencing, imaging platforms, and high-performance GPU computing. Research Environment: An international