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understanding of GPU and VRAM constraints. Equally, you will need to explain all of it clearly to people with very different levels of technical confidence, and to think carefully about licensing, copyright, data
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-line tools and model repositories, and a working understanding of GPU and VRAM constraints. Equally, you will need to explain all of it clearly to people with very different levels of technical
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Sciences. At the division, we conduct research and education on the energy generation, conversion, and utilization in different electro- and thermo-mechanical systems where the study of heat transfer, fluid
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collaborators and strong access to compute through national GPU systems (NAISS, e.g. Berzelius and Arrhenius) and local GPU infrastructure. Project description The position offers significant scientific freedom
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computing. You will join a collaborative team that values technical excellence, innovation, service, and shared success. We encourage new ideas, knowledge sharing, and different perspectives, and we
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trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. Depending on the day, we
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Interactions external link groups, with close interaction with bioinformatics, microbial ecology and experimental crop research at the UU and NOAH partners. You will have access to Utrecht University GPU/HPC
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GPU infrastructure. This Postdoc position is part of the eSSENCE graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from the foundational
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the Platform team within AI Products at AISG. In this role, you will be collaborating with different internal teams to design and implement optimized inference workflows and support the team to build
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that accelerate scientific discovery and societal impact. Help to identify appropriate hardware, software, and cyberinfrastructure platforms for different stages of research and development, including data