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contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber
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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
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for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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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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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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collaborative, impact-focused problem solver who wants to be part of a dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https
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an environment that is diverse, inclusive and respectful. Learn more about our lab here: https://bioniclab.seas.harvard.edu/ We are recruiting fellows from diverse backgrounds interested in solving tough problems
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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Control Lab at Harvard University, under the direction of Dr. Maurice Smith, is seeking a postdoctoral fellow to study human motor learning and motor control. The lab is in the Harvard Paulson School