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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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of technical requirements for different use scenarios of AI applications. 3) Study and comparison of server architectures, GPUs, and storage solutions suitable for AI. 4) Implementation of virtualization and
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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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scalable compute solutions integrating CPU/GPU resources, high-speed interconnects, parallel storage, scheduling, and supporting infrastructure. Establish technical standards, architectures, and engineering
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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
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you will operate what you design. We expect and support open-sourcing and publishing this work. The environment A large NVIDIA GPU cluster (B300/H200/H100 class) running self-hosted open-weight models
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department currently manages a SLURM-based cluster comprising CPU, high-memory (HMEM), and GPU nodes, supporting a diverse range of computational research. About the role As the Institute’s computational
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GPUs (e.g., B200, RTX 6000 Blackwell Pro, H200) and CPU architectures that, even if they increase complexity, generate the kinds of problems we love! This role in our Operations Team provides support for