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Field
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supportive team environment that promotes collaboration and knowledge sharing. Access to world-class computational infrastructure, GPU-based computing environments, and unique high-quality cryoET datasets
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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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FLAME-GPU Accelerated Agent-based Modelling of Material Response to Environmental and Operational Loading EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce
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, GPU/FPGA acceleration or high-performance computing. Desirable Knowledge, Skills, and/or Abilities 1. Active government security clearance at Secret level or higher. 2. Demonstrated success in
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Administrator Working Title HPC Systems Administrator I or II Career Progression Track P00 Track Level P3 - Career FLSA Code Computer Employee Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time
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Language Model (LLM) GPU cluster to ensure stable and reliable operation of training tasks; (b) handle GPU node failures, IB network anomalies, CUDA/NCCL errors and Kubernetes scheduling failures, perform
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to support efficient model training iteration; (b) lead the construction of the GPU computing cluster centered around a Kubernetes + NVIDIA GPU Operator, including node planning, resource management
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environments, including use of high-performance computing clusters and, ideally, GPU-enabled workflows. *Experience with GitHub, version control, and repository management for collaborative and reproducible
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Computer (HPC) with its sizable cluster of CPUs, GPUs, storage arrays and high speed networking as well as our cloud (AWS) based Data Safe Haven, used for researchers working on sensitive data. As Research
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modeling). Experience working with HPC/GPU resources and job schedulers (e.g., Slurm) and/or cloud-based deployments. Track record of contributing to peer-reviewed publications as a computational specialist