132 parallel-computing-numerical-methods-"Prof" Fellowship positions at Harvard University in United States
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. Positions are available for recent Chemistry, Physics, Electrical Engineering, Biophysics and Computer Science Ph.D.’s who are interested to work in synthetic artificial biochemistry-free life mimics (life
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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our lab. Potential applications of interest include artificial extracellular matrices for regenerative medicine, breadboards for localized molecular computing, and nanophotonic devices. Present
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terrace, fitness center, locker room, bike storage, and close proximity to numerous restaurants and cultural attractions. Why you’ll like working with us: At the Wyss Institute, you’re a member of a
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terrace, fitness center, locker room, bike storage, and close proximity to numerous restaurants and cultural attractions. Why you’ll like working with us: At the Wyss Institute, you’re a member of a
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quasi-experimental methods to identify causal effects and test the predictions of economic and sociological models. Examples of current research projects include: long-term impacts of neighborhoods and
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. accredited colleges, universities, and U.S. Government laboratories across the country. Participants in the IC Postdoc Program have achieved numerous significant accomplishments, including: More than 450
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of private-sector data to understand disparate impacts in the recent economic recession and recovery. Much of the team's ongoing research uses quasi-experimental methods to identify causal effects and test the
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-derived cells (iPSCs, myogenic progenitors), genetic mouse models, and phenotypic drug screening methods. In addition, we are examining severe muscle damage that results in a less efficient regenerative
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for Biomedical Imaging (Harvard/MIT/Mass General). In parallel, there will be opportunities to analyze and publish existing data upon identifying areas of mutual interest. The appointment is for one year with a