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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
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machine learning algorithms for application to sonar and underwater acoustics, as well as the accompanying data analysis to effectively characterize their performance in the Advanced Technology Laboratory
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algorithms and parallel/distributed variational algorithms in AI/ML for application workflows and large-scale HPC and QC systems Develop quantum machine learning (QML) algorithms for optimization of multi
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vision, graphics and visualization, systems, distributed algorithms, and scientific and biomedical computing. Research in the department is and has been funded by numerous agencies, including the National
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control systems, especially EPICS. Familiarity with synchrotron light science (e.g., ALS) preferred. Experienced in RF technology, magnetics, distributed controls, and algorithm design. Strong academic
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with compiler level languages, accelerated computing (preferably with OpenMP or OpenACC) and distributed computing (MPI). A thorough understanding of the particle-in-cell algorithm, its inherent
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develop new communication theory and signal processing algorithms. The goal will be to develop theory, algorithms, and network architectural concepts to deliver ubiquitous network services across the globe
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
involves integration with cloud services, distributed storage networks, and the dedicated computing cluster supporting Array operations. The Data Production Engineer will bring the real-time analysis
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the power of cutting-edge digital technologies to implement and manage FAIR (Findability, Accessibility, Interoperability and Reusability) environments for data management and algorithm preservation and
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group , led by Prof. Glenn van de Ven, is part of the Department of Astrophysics . The research group constructs detailed dynamical models of galaxies and stellar clusters to infer the distribution