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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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Do: Contribute to one or more NESAP workflow projects (https://www.nersc.gov/what-we-do/support-for-scientists/nersc-science-acceleration-program/nesap-for-doudna) using NERSC HPC resources, edge
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their efforts on the education of students and the performance of life-changing research across a wide range of disciplines including medicine, engineering, physical sciences, energy, computer science, and social
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disease insights. The lab has state-of-the-art computing capabilities with an in-house cluster serving 80 CPU cores and 1.5TB of RAM, as well as a newly acquired NVIDIA DGX box with eight H100 GPUs and 224
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. Experience with graph-based data analysis or anomaly detection methods. Exposure to high-performance or GPU-based computing environments. Demonstrated ability to contribute to publications or technical reports
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, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
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options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits
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the computer science research conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings