168 parallel-computing-numerical-methods-"Multiple" Fellowship positions at Harvard University
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/Area Computer Science Position Description Accepting applications for postdoctoral position in Reinforcement Learning, Probabilistic Methods, and/or Interpretability. Information on the lab can be found
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robust leadership development and training to rising public leaders each year. The fellowships offer students an intensive, cohort-based co-curricular program grounded in servant leadership and
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parallel screening platform to discover orthogonal protein binders. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing
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Details Title Postdoctoral Fellowship in Computer Science - Procaccia Lab School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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Patel’s group to produce highly impactful biomedical informatics research that presents new innovations in methods and novel findings that inform disease etiology. The candidate should be interested in
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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Details Title Postdoctoral Fellow / Visiting Scholar (unpaid), Aga Khan Program for Islamic Architecture, Harvard University School Faculty of Arts and Sciences Department/Area Aga Khan Program for
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position. We are most interested in applicants who have experience in computational methods development, in human genetics or a different field. Possible areas of research include: 1. Developing methods
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parallel screening platform to discover orthogonal protein binders. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods