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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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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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experiments. You will experience designing and operating massive-scale GPU and combined CPU/GPU workloads across these services. You will design and debug platforms, and will work closely with researchers as
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managed as software-defined infrastructures, and integrated as complete computational experiments. You will experience designing and operating massive-scale GPU and combined CPU/GPU workloads across
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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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to introduce state-of-the-art AI tools, accelerating technology transfer and hands-on learning opportunities. Design and deploy high-performance AI systems using GPUs and hardware accelerators. Job Description
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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 competitive wholesale electricity
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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