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of the following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing
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for mechanical, electrical, cooling, and infrastructure systems that underpin Cornell’s computing environment, including High-Performance Computing (HPC) and Graphics Processing Unit (GPU)‑intensive workloads
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
20 Jan 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
balance Training and international experience in public–private partnerships Mentoring for career development Access to high-performance computational resources (with GPUs) A collaborative environment
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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balance Training and international experience in public–private partnerships Mentoring for career development Access to high-performance computational resources (with GPUs) A collaborative environment
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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Infrastructure - Collaborate with research computing teams and HPC centers to architect AI infrastructure solutions that support both administrative and research computing needs, including GPU-accelerated
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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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members in designing and integrating solutions into the AI(X) compute, software and data infrastructure stack, hardening these solutions, testing these on modern high-performance GPU compute clusters, and