142 parallel-computing-numerical-methods research jobs at Harvard University in United States
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, statistical analysis of data, mathematical modeling, and communication of results, with the aim of guiding policy for climate change adaptation. Experience with theoretical and experimental methods
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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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Supporting Dental, Oral, and Craniofacial Research Using Bioinformatic, Computational, and Data Science Approaches. See Notice NOT-DE-20-006 . April 1, 2020 - Notice of Special Interest: Developmentally
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of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, and the neurobiological basis of intelligence. Research and development of new AI or ML
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uses 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
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economic recession and recovery . Much of the team’s ongoing research uses quasi-experimental methods to identify causal effects and test the predictions of economic and sociological models. Examples
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Details Title Postdoctoral Fellowship in Power and AI Systems School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science/ Electrical Engineering
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Research Fellow provides cross-functional support on a wide array of IQSS research projects as directed by various faculty/program leads, including IQSS Faculty Director, Professor Gary King. Based at IQSS
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his bioengineering lab are seeking a highly motivated postdoctoral researcher with a strong background in neuroscience. The ideal candidate will have extensive training in their Ph.D. program and be
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be