2,344 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" Postdoctoral research jobs in United States
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Associates will teach one seminar per year, which is one section of SHUM 2750 Introduction to the Humanities in the spring term. As well, we expect each to supervise the one-credit course SHUM 4750 for guiding
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service, or genetic information in its administration of educational policies, programs, or activities; admissions policies; scholarship and loan programs; athletic or other University-administered programs
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
to promote faculty, staff, and learner development in a diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning, and create personal and professional sustainability
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enzyme activities and conduct directed evolution, structure-guided protein engineering, and machine learning-guided protein engineering studies to improve enzyme and pathway function. The ability
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competing structural phases and the vibrational and electronic structure in materials with defects and disorder. This effort will further seek to implement strategies to leverage machine learning techniques
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
care, education, and research. We strive to promote faculty, staff, and learner development in a diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning, and
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machine learning. In addition to leading research initiatives, the postdoc is expected to collaborate closely with graduate students, faculty, and industry and DoD partners. Key responsibilities include
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machine learning. In addition to leading research initiatives, the postdoc is expected to collaborate closely with graduate students, faculty, and industry and DoD partners. Key responsibilities include
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a