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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 3 months ago
tools for spacecraft applications, specifically leveraging topology optimization and lattice structures. Building upon prior work at JPL, including the open-source lattice design tool UnitcellHub and an
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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engineers, the position requires tackling these challenges by applying machine learning techniques to accelerator tuning and control. You will study beam-based diagnostics to optimize machine performance as
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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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representation learning, and real-world data modeling to stratify risk and optimize MHT formulations. The candidate must thrive in a multidisciplinary, fast-paced research environment and work independently and
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School of Medicine. The project will focus on optimization of peptide ligands targeting promising cancer antigens followed by subsequent radiolabeling and pre-clinical validation. The Beinat lab employs
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Sriperumbudur. Potential research projects include (but are not limited to) developing theory and methods for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows
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abstraction, and (2) examining how neural replay?the spontaneous reactivation of learned neural patterns?supports human continual learning by optimizing task representations offline and guiding decision-making
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. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized