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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
: Familiarity with ice-ocean interaction physics or polar oceanography. Experience with high-performance computing, GPU-accelerated models (e.g., Oceananigans.jl), or advanced flow measurement techniques (e.g
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NASA's Jet Propulsion Laboratory, focused on developing a next-generation, GPU-based climate model that learns physics from data to improve the accuracy of its projections. Will collaborate with
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Jet Propulsion Laboratory, focused on developing a next-generation, GPU-based climate model that learns physics from data to improve the accuracy of its projections. Will collaborate with oceanographers
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
or polar oceanography. Experience with high-performance computing, GPU-accelerated models (e.g., Oceananigans.jl), or advanced flow measurement techniques (e.g., PIV, LIF). Interest in mentoring graduate
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astrophysical free boundaries. Responsibilities include running high-resolution GPU-accelerated simulations on exascale computing systems, developing and applying geometric measure theory tools to quantify
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(e.g. systems biology), or ordinary/stochastic differential equations. Experience in computational, statistical, or machine learning method development in any discipline. Experience in GPU computing
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that address real-world challenges and deliver positive business outcomes. The Institute for Insight is equipped with a computer cluster that includes multiple GPUs, designed for big data analytics for both
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. Zou, which includes access to high performance computational resources with GPUs, conference travel support, and great opportunities for collaboration and networking with experts in Industrial
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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state
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environments, cloud computing, or GPU-accelerated machine learning Background in Monte Carlo Tree Search (MCTS) or reinforcement learning for sequence generation Familiarity with biological sequence alignment