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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
the group of Dr. Tengfei Li at the University of North Carolina at Chapel Hill. The successful candidate will develop and apply advanced statistical and machine learning methods for infant cognitive
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. Applicant(s) should possess a Ph.D. degree, or equivalent, in biological or computer sciences or a related discipline. Experience in any of the following fields, including 1) biological image acquisition
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or precision oncology Experience with biological image analysis and machine learning for computer vision Excellent communication skills Excellent verbal and written English language skills (German is not
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&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
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: detection of objects and relations between objects, and use of these relations to infer new knowledge (i.e. reasoning); (ii) explore object affordances, learn the consequences of the actions carried out and
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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and
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Postdoctoral Research Associate to join our research group working at the intersection of advanced manufacturing, computational modeling, and machine learning. This position offers an opportunity to contribute
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/or networked microgrids. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr. Peng Zhang in the Department of Electrical and Computer Engineering . The