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Field
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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
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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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for operating and developing a research infrastructure comprising CPU- and GPU-based HPC systems, petabyte-scale storage, scientific web services, secure environments for sensitive data, and emerging AI-related
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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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, e.g in a GPU architecture, and their applications to magnetic phenomena is meriting. About the employment The employment is a temporary position of two years according to central collective agreement
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find and assess the most promising habitable exoplanets around solar-like magnetically active stars? Join us to build next‑generation GPU‑accelerated models of stellar dynamos and connect them
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
perturbative matching. Experience with lattice QCD software frameworks (e.g., Chroma, QUDA, Grid) and GPU computing. Experience with statistical analysis of large Monte Carlo datasets, including inverse-problem
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Administrator, you will help develop, operate and continuously improve complex Linux-based research computing infrastructure, spanning established HPC and HTC platforms and emerging AI and GPU-enabled services
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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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microscopy, X-ray imaging, and light microscopy). It supports researchers across three compute scales: laptop-based prototyping (S-Gym), single-GPU workstations (M-Gym), and multi-node HPC at the National