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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 14 hours ago
supporting GPU computing environments, including NVIDIA drivers, CUDA, GPU scheduling, monitoring, and performance optimization; familiarity with AMD ROCm is desirable. Experience with container technologies
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monitoring plugin. Based in the PRISMA Computer Vision lab within the School of Computer Science at the University of Sheffield, the post offers access to high-performance computing and GPU facilities
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project GPUs (B200s and cloud credits) and GPUs from the Department of Computing and the College of Engineering (A100s and H200s) The opportunity to continue your career at a world-leading institution and
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Position Summary Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network
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24 Jul 2026 Job Information Organisation/Company Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH Research Field Computer science » Computer architecture Engineering » Computer engineering
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, or approximate computing. Knowledge of hardware security, fault tolerance, dependable computing, or hardware reliability. Experience with GPU, FPGA, embedded, or specialized AI accelerator platforms. Experience
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AI Singapore (AISG) is a national AI programme launched by the National Research Foundation (NRF), Singapore, to build and anchor deep national capabilities in AI. AISG is supported through a
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-Champaign invites applications for one open-rank (assistant, associate, or full professor level) tenure-track, full-time faculty position. Applications broadly in computational mechanics and materials will
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performance GPU computing — whether through thousands of commercial GPUs or a handful of Nvidia NVL72 racks — and specialized signal processing hardware. Automation: Develop and implement automated processes
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systems and underwater imaging. 4. Linux system administration and scientific computing workflows, including environment management, GPU-accelerated workloads, and remote/headless operation. 5. Familiarity