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Glick Eye Institute is to train tomorrow’s ophthalmologists and advance treatment and prevention of eye diseases and vision disorders through basic, translational, and clinical research. Our vision is to
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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: https://rademaker.unige.ch/ The candidate · holds a PhD (or an equivalent degree) in Theoretical Quantum Matter Physics by the starting date; · has excellent spoken and written English
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
articulated in the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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and project developers in reusing them in new projects. Taking the Chalmers campus as a starting point, we are developing scalable, AI-powered methods, such as computer vision for street-view imagery
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, intraoperative video, OR traffic signals, EHR data, and patient/surgeon surveys with explainability and equity at its core. Among the key duties of this position are the following: Design and train vision–text
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College:Carver College of Medicine Department:Inst for Vision Research Salary Salary:$62,232.00 to Commensurate Position Details Full/Part Time Status:Full Time Percent Time:100% Position Description: Post
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in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses on methodological development in cryo
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities