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prioritize candidates who specialize in Artificial Intelligence (AI) and Machine Learning (ML), including but not limited to areas such as deep learning, natural language processing, computer vision
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-earning appointment in the Department of Biology and will be expected to contribute to interdisciplinary research through sustained collaboration with UWF’s Center for Computational Intelligence. We
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be considered at junior or
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Post-Doctoral Associate in the Center for Artificial Intelligence and Robotics (CAIR) Employer NEW YORK UNIVERSITY ABU DHABI Location Abu Dhabi, United Arab Emirates Closing date 27 Aug 2026 View
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equivalent experience in machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be
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, and bio-inspired robotics. Research at our Tübingen site focuses on theoretical and computational aspects of intelligent systems, covering topics such as machine learning, computer vision, control
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advancing the state of knowledge in their chosen research area. Criteria of the candidate: PhD in: Computer Science, Artificial Intelligence, Data Science or related fields (Computational Physics
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Post-Doctoral Associate in the Center for Artificial Intelligence and Robotics (CAIR) Employer NEW YORK UNIVERSITY ABU DHABI Location Abu Dhabi, United Arab Emirates Closing date 28 Oct 2026 View
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 22 hours ago
02, 2021 Description The Computer Vision-Core Artificial Intelligence Research ( Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and
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development of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB