119 parallel-computing-numerical-methods Fellowship positions at Harvard University in United-States
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regimes of deep networks. Basic Qualifications: A PhD is required. We seek candidates with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics
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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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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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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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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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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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. 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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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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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