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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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. Professor Christoph Goebel (TUM) will act as the host at TUM. Possible topics of research include, but are not limited to • Exploiting GPUs for large-scale optimization • Value stacking of storage in
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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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A100/H100 GPUs, and 8.5 PB of attached research storage; https://docs.itrss.umsystem.edu/pub/hpc/hellbender). A wide variety of additional research instrumentation is available on campus at the MU
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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