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The Department of Computing wishes to recruit a Cloud and GPU Infrastructure Manager to be responsible for the administration, maintenance, and optimization of both our internal GPU infrastructure
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
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AI pipelines (similar to the attached prototype). Enable users to configure model parameters, connect modules, and monitor training progress. Display performance metrics (e.g., inference time, GPU
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projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect). The is also well-provisioned with computational resources and you
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projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect). The is also well-provisioned with computational resources and you
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of research computing at LSE. Your expertise will be key in future-proofing our research hardware environment, ensuring high availability, scalability and security across HPC clusters; GPU acceleration, high
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the Northern 8 cluster, members of Durham University can also submit projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect
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reproducible computational pipelines for HPC/cloud environments. Experience with AI explainability methods, Git repositories, GPU acceleration, and the ability to draft manuscripts for publication are also
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software solutions and working in a team Based at our Riseholme Campus, you'll have access to exceptional facilities including robotics labs, GPU clusters, and a working farm for real-world testing. We offer
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management at scale and GPU technology in virtualised environment are highly desirable. As part of this recruitment we are looking to appoint a Senior Research Infrastructure Developer with specialisations in