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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
students, and collaborate with AI faculty in vision, robotics, and machine learning across the department. Minimum Education and Experience Requirements Applicants should have, or expect to receive before
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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less). In the ANR/CEA-funded BrainSync collaborative project, we are interested in characterizing the neural representations of uncertainty6–8 and value that emerge from learning and guide decisions. Our
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to different diseases under abiotic stresses. This postdoc position offers the opportunity to learn the needs for keeping plant breeding innovative in the future, and to apply your research skills in the domain
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. Conduct transportation resilience assessment and enhancement studies based on GIS, complex network analysis, and machine learning. Simulate human mobility in response to extreme weather events (e.g
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
discovery, machine learning, and data science. The position will provide the opportunity to develop applied research skills in machine learning, interact with an international network of collaborators, and
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-learning models (e.g., graph neural networks, equivariant architectures) in collaboration with computer science researchers. Applying developed models to problems in Earth and planetary interiors, such as