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Missouri University of Science and Technology | Rolla, Missouri | United States | about 17 hours ago
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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Sciences of the University of Strasbourg. Close collaborations with the various project partners are also planned throughout the PhD. A dedicated computer equipped with high-performance GPU cards will be
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goals on our lab website (https://hscrb.harvard.edu/labs/arlotta-lab/). In addition, the Arlotta lab is actively working to foster an equitable and inclusive community. Basic Qualifications · Ph.D. degree
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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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provide GPU computing for machine learning on Aalto's Triton high-performance computing cluster, alongside industry-standard circuit simulation tools (Cadence, Synopsys, etc.) on our own computing cluster
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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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, 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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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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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 7 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