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Field
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the College of Engineering. UNLV GPU Cluster (named RebelX) is also available for A.I. research and education. Detailed information about the CEEC Department can be found at: http://www.unlv.edu/ceec MINIMUM
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of the Empire AI Consortium, researchers have access to state-of-the-art computational infrastructure, including large-scale GPU clusters and high-performance computing resources. The Institute has
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gun, associated diagnostics resources, and well-equipped high-speed and reacting flow laboratories. The National Center for Supercomputing Applications houses the most performant GPU-based systems and
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, or emerging technologies); Python fluency plus a second server-side language; cloud & GPU proficiency; record of mentoring. Preferred – Master’s degree; expertise in TypeScript and good architectural
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%) Use tools to identify opportunities to improve performance or understand resource use (utilization of cores, memory, GPU, etc.) in AI workflows. Engage with Ohio, regional and national professional
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of unparalleled computing resources in the academic environment by optimizing AI/ML models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing
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troubleshooting and repair skills. Experience supporting the installation, configuration, and monitoring of Nvidia GPU cards and required drivers and software within Linux. Experience supporting researchers in
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on the 1D or analytical model) Hybrid simulation approach (e.g., which combine CFD and 1D simulations) High Performance Computing and/or GPU programming for this domain Machine learning algorithms
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic