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-throughput processing. Enhance the computational efficiency of compute environments by optimizing resource allocation (including CPU/GPU utilization), parallelizing data pipelines, and resolving processing
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, and administers CPU/GPU HPC clusters, including management and compute nodes, storage infrastructure, interconnects such as InfiniBand, and physical infrastructure in the datacenter and related systems
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acceleration. Practical expertise in real-time control systems or adaptive feedback loops. Hands-on skills in data acquisition systems and high-speed communication protocols. Competence in GPU computing
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addition to the pan-university Hamilton GPU resource (8 NVIDIA H200 NVL) which both complement our departmental NVIDIA CUDA Compute Cluster (80+ GPUs up to NVIDIA A100) to cater for the increasing GPU compute demands
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9 Jul 2026 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Chemistry » Computational chemistry Computer science » Other Physics » Other Researcher Profile
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one or more of the following areas: Programming, Algorithms and computational complexity, Programming languages and compilers, Computer graphics, and Parallel and GPU computing. A typical teaching
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School of Computing and Communications Location: Bailrigg, Lancaster, UK Salary: £39,906 to £46,049 (Full-Time/Indefinite with End Date) Closing Date: Sunday 28 June 2026 Interview Date: Friday 10
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- 12:00 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Hours Per Week 40 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number
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, MIG, node affinity). Experience optimizing GPU utilization, memory management, and cost efficiency for compute-intensive workloads. Preferred Competencies Ability to collaborate and interact effectively
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based