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Engineering and Systems Data Science / Computer Science , Machine Learning Appl Deadline: 2025/11/10 11:59PM (posted 2025/09/24, listed until 2026/03/24) Position Description: Apply Position Description Duke
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experience in areas that align with the faculty (https://neuroscience.barnard.edu/people ), specifically in the areas of vision, learning, and development at the molecular, cellular, systems, cognitive
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at the interface of biological physics, agent-based simulations and machine learning to turn quantitative imaging data into a mechanistic, testable model of spindle positioning. In particular, we expect
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and temporal patterns from multisource data, spatiotemporal data analysis and mining and model learning and physical parameter prediction. Responsibilities consist of conducting computer modeling
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factors. Though not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and
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education and economic development needs. Federally designated as a senior military college, one of the university's signature leadership programs is its 800-member Corps of Cadets on UNG's Dahlonega Campus
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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, machine learning, energy technology or related subjects Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression Experience in
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/ThreeBodyTB.jl), cluster expansion, classical potential development, and machine learning. In addition to work on specific problems, I work on developing new first principles-based modeling approaches, including
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code