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the university's research priorities and technological advancements. Performance Optimization: Analyze and optimize the performance of AI models and HPC applications focusing on GPU-enabled computing. Implement
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, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs) to improve power efficiency and preserve power integrity. Integrated voltage regulators (IVRs
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, mathematical sciences, or applied mathematics/engineering, and who are motivated to engage in AI research in earnest. We also welcome applicants with the following experience: - Operation and use of GPU-based
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finite elements) as well as alternative discretization methods (e.g., Lattice Boltzmann Methods), and high-performance computing. A selection of possible research areas can be found on our website: https
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computing (HPC) systems, including GPUs, and programming, such as using CUDA, MPI, AI/ML/DL, and advanced debuggers and performance analyzers. Familiarity with working on open-source projects. About UF
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frameworks (e.g., PyTorch). Engineering skills: GPU/cluster training, experiment tracking, data engineering. Ability to formulate research questions, run empirical studies at scale. *for students with
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, and interacting with pilots and passengers. Operates and becomes familiar with ground support equipment, such as the aircraft tug, ground power unit (GPU), lavatory service cart, de-icing cart, forklift
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production are available at http:/www.fbk.eu/research-centers . In particular, the FBK Cyber Security Centre (CS) develops digital technology and cyber security to foster collaboration between the various
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: Applications accepted all year round Details In this project you will combine state of the art software development approaches for GPU programming with the study of interactions of high-energy particles with
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Transformation program that seeks to increase equity in STEM fields through collaboration (https://www.umass.edu/advance/ ). For more information on work-life balance at UMass Amherst, see https://www.umass.edu