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Position Details Position Information Recruitment/Posting Title Lead Software Developer – GPU-accelerated Free Energy Simulation and Machine Learning Methods Department Quantitative Biomedicine Inst
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HPC infrastructure; • installation, configuration, administration, and monitoring of: - CPU and GPU computing clusters, - storage systems, - virtualization and cloud computing platforms, - orchestration
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, automating, and optimizing the GPU and AI and computing infrastructure used by researchers across the university, along with the high-performance computing systems that support it. This position will be filled
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, automating, and optimizing the GPU and AI and computing infrastructure used by researchers across the university, along with the high-performance computing systems that support it. The position will be filled
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and ethically. Its core is a studio of high-performance GPU workstations hosting open-source models locally (image, video, audio and language) where staff and students can see, adjust and interrogate
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development and GPU-accelerated inference to change what can be attempted by a small research group. The postholder will derive physical predictions, direct the construction of the software needed to test them
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GPUs (B200s and cloud credits) and GPUs (A100s and H200s) The opportunity to continue your career at a world-leading institution Sector-leading salary and remuneration package (including 43 days off a
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foundations. The Centre is committed to working with AI systems openly and ethically. Its core is a studio of high-performance GPU workstations hosting open-source models locally (image, video, audio and
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capabilities. Technical Skills - Desired Experience with Cray EX supercomputers with NVIDIA GPUs. Experience with Kubeflow pipelines and Kubeflow Training Operator. Experience with distributed inference
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port scientific applications to maximize performance across CPU, GPU, memory, storage, and I/O. Contribute technical expertise to faculty projects through the RCC Consultant Partnership Program and other