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; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational
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, navigation and control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 25 days ago
involves repetitive bench tasks such as pipetting, extended periods standing or seated at a laboratory bench, and extended periods at a computer workstation for data analysis. Reasonable accommodations will
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Infrastructure Computer Vision Data Analytics for the Built Environment You should possess: A completed PhD in a relevant discipline. Strong research expertise in digital engineering and built environment research
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throughout their evolution. Our vision combines ideas from differential geometry, numerical analysis, scientific computing, dynamical systems, and applied mathematics to develop new mathematical frameworks
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
involves repetitive bench tasks such as pipetting, extended periods standing or seated at a laboratory bench, and extended periods at a computer workstation for data analysis. Reasonable accommodations will
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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or hearing. Manual dexterity and vision sufficient for standard laboratory and computer operations. WORK ENVIRONMENT: Lab environment. Moderate noise. Travel to various sites/locations. Special Conditions
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Nevada. For more information, visit us on line at: http://www.unlv.edu EEO/AA STATEMENT The University of Nevada - Las Vegas (UNLV) is committed to providing a place of work and learning free
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position focused on advancing crop production and physiology through field experimentation, computation (statistics and machine learning), and process-based models. The successful candidate will have an