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Details Title Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability School Harvard John A. Paulson School of Engineering and Applied Sciences Department
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Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | 3 days ago
statistical simulation and method validation techniques. This is an educational and developmental program in mathematics and statistics, including biometrics and biostatistics, in which you will receive related
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exclusive 2-year program geared toward PharmD and PhD graduates with a penchant for clinical research in the pharmaceutical and biotechnology industries. Established in 2009, the fellowship has paved
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Details Title HMS - Postdoctoral Fellow in Health Care Policy - Statistical Methods School Harvard Medical School Department/Area Department of Health Care Policy Position Description The Department
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About the lab We are a newly established computational research group at the Translational Genomics Research Institute developing and applying pangenome methods to study genome variation and
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detection and intervention promise to improve outcomes. We welcome applications from PhD and MD PhD graduates interested in this problem, particularly those who may bring a new expertise or perspective
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, Pennsylvania 15237, United States of America [map ] Subject Areas: Mathematics; Formal Methods; AI Appl Deadline: (posted 2026/01/15 05:00 AM UnitedKingdomTime, listed until 2026/07/16 04:59 AM UnitedKingdomTime
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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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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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skills in quantitative methods and data analysis software, writing skills 2. Research experience in related areas 3. Demonstrated ability to work independently, under supervision, and as part of a team