119 parallel-computing-numerical-methods-"Prof" Fellowship positions at Harvard University
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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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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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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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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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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and Regenerative Biology has an exciting and broad multiomics program focused on brain aging. Approaches will include experimental and computational efforts across multiple labs at Harvard's Faculty
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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
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especially encourage candidates with proven experience in applying computational and experimental methods to social scientific questions – including aptitude in working with large-scale datasets and text