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Field
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2026, UTC will deploy a state-of-the-art scientific computing and storage infrastructure, comprising a high-memory, GPU-enabled HPC computing node and a modular, scalable RAID-based storage system
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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed
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towards a more sustainable future. The Core Unit High Performance Computing (HPC) at the Max Planck Institute of Geoanthropology is the central support unit and technical partner for researchers. We help
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of computational computing clusters including, but not limited to GPU clusters, General HPC clusters, and SMP environments. Experience with Centos or similar Linux distributions. Experience with programming jobs
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facilities. Core responsibilities include the deployment and maintenance of small-scale HPC and compute nodes, GPU workstations, Linux and Windows servers, research data storage and backup solutions
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to apply; we value employees with a willingness to learn. Understanding of technologies employed in research in higher education Familiarity with distributed computation solutions Familiarity with GPU
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to apply; we value employees with a willingness to learn. Understanding of technologies employed in research in higher education Familiarity with distributed computation solutions Familiarity with GPU
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storage and archiving solutions to collaboration and analytics tools. ARC also delivers Baskerville; a leading GPU accelerated National Compute Resource (NCR) and supports researchers using specialist
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creativity, while also contributing to CMU’s dynamic program that emphasizes critical thinking, interdisciplinary collaboration, and socially engaged communication practices. Position Expectations: Teach
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computing environments for advanced research. B2 Knowledge of scaling and optimising software to take advantage of GPU / HPC infrastructure. Skills Essential: C1 Excellent written and verbal communication