124 machine-learning "https:" "https:" "https:" "UCL" Fellowship positions at Harvard University
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salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/benefits
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Additional Qualifications Strong confidence with and/or facility to learn Matlab or Python-level programming Strong interest and experience in systems neuroscience, electrophysiology, or primate behavior
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postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Minimum Number of References Required Maximum Number
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on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic
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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
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performance enhancement. The Postdoctoral Researcher will coordinate and lead a research project at the intersection of wearable sensing, controls, machine learning, AI, robotics, and movement science. They
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at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective bargaining and matters affecting your
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Laboratory directed by Dr. Capellini and located in the Peabody Museum on Harvard University’s Cambridge, Massachusetts campus. The lab’s website is: http://projects.iq.harvard.edu/evolutionary_genetics/home
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic