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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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Location: South Kensington Campus About the role: Applications are invited for the above post to work with Professor Christos Bouganis and his team at Imperial College London for a project funded by the Commission of the European Communities. The successful candidate will be integral to...
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processing including segmentation. The team is well equipped with high-end workstations with 1Tb RAM and 4090 GPUs, and a 4-8 GPU server for more complex tasks. The University of Warwick is part of
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on hardware which may include CPUs, GPUs and FPGAs. In particular we are interested in applicants who have experience of modern coding practices and software techniques. The post-holder will work with Prof. Ben
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rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels. This role offers a unique opportunity to
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computing resources, with additional support involving HPC systems such as configuring GPU nodes, managing Slurm queues, containerising teaching notebooks, and enabling advanced pipelines Promote Robust
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free text of both biomedical literature and electronic patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling
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as code” approach to systems automation. You’ll be working across a range of predominately Linux based systems, including HPC and GPU accelerated compute, large-scale and high-performance storage, and
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has embraced the “infrastructure as code” approach to systems automation. You’ll be working across a range of predominately Linux based systems, including HPC and GPU accelerated compute, large-scale
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patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling for ML / LLM algorithms working over free-text clinical