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skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application
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computing, and parallel programming paradigms Strong publication record in reputable avenues Strong writing skills Strong skills in model development, data analytics, machine learning, and visualization
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writing skills Skills and abilities: This will vary based on the hiring manager’s preferences and should include things that can be learned or trained for. Specifications Minimum Required Education: PhD in
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systems, machine learning, and control theory. Experimentally validating these methods through field experiments. In addition to conducting research, the Postdoctoral Scholar will collaborate closely with
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-to-system solutions to prepare and submit your application to Grants.gov and track your application in eRA Commons. Learn more . Table of Contents Part 1. Overview Information Part 2. Full Text
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the Fellowship start date of August 29, 2025. Recent PhDs from any discipline (including but not limited to Africana studies, anthropology, Asian studies, business administration, comparative literature
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analytics, and machine learning, the Grid Interactive Controls group delves deeply into understanding intricate grid-edge operations. Researchers are dedicated to laying the groundwork for optimal X2G
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
of patient 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
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recommendations to non-technical audiences effectively. 5. Continuous Learning and Expertise Development: o Stay updated on state and federal Medicaid policy changes, trends, and innovations, especially those
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
emphasis on remote sensing. 2. Experience of using multiple sources of remotely sensed data, particularly optical, Lidar, and Radar data. 3. Sound statistical skills and use of Machine Learning/Geospatial AI