140 phd-in-computer-vision-and-machine-learning Fellowship positions at Harvard University
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. We are looking for exceptional candidates with background in machine learning and/or computational biology. Research will focus on both top-down and bottom-up mapping of local interactions between
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Born in Chicago, Dr. Yerby was the youngest of four children. After finishing high school, he enrolled at the University of Chicago and then went on to study medicine at Meharry Medical College in Nashville, Tennessee—one of only two black U.S. medical colleges in existence at the time. After...
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, individuals and other contributors have joined the Charles A. King Trust in supporting the Postdoctoral Research Fellowship Program. Proposals focused on cancer or vision are highly encouraged due
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proposed mentors from current faculty associated with the Kempner Institute or working on machine learning, artificial intelligence, or computational neurobiology at Harvard. A research proposal of no
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PhD in theoretical neuroscience, physics, computer science, or related fields is required. Applicants must demonstrate strong analytical and numerical skills. Additional Qualifications Special
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Qualifications Ph.D. or M.D./Ph.D. in areas such as bioengineering, biochemistry, cell or computational biology or related fields Additional Qualifications CV Research summary of PhD work Cover letter describing
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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at Harvard. For further information, please contact ydu@seas.harvard.edu. Basic Qualifications PhD in Computer Science, Electrical Engineering, Mechanical Engineering or a closely related field Additional
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interaction in chemistry and in cellular signaling. We are also applying mathematical formalism to reason about functional organization in biology. We welcome applications from recent PhD graduates who bring a
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a