373 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Harvard University
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PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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ssantagata@bwh.harvard.edu Salary Range Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines Minimum
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of and experience with quantitative methods (simulation modeling, optimization, and machine learning) preferred This is an annual term position reviewed each academic year on or before June 30th, with
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on performance. Please take a look at the type of work Prof. Stantcheva does on her website: https://www.stefanie-stantcheva.com/ as well as on her Social Economics Lab website http://socialeconomicslab.org
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computational approaches. See our lab web page (https://projects.iq.harvard.edu/gaudetlab ) for more information about our publications and research interests. Basic Qualifications Candidate must hold a PhD in
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: Apply Description Join us as a postdoctoral fellow in Professor Susan Murphy’s Statistical Reinforcement Learning Group. Our research concerns sequential decision making in digital health, including
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vibrant intellectual environment. Basic Qualifications Please see the fellowship page for more information: https://www.huri.harvard.edu/jacyk-distinguished-fellowships Additional Qualifications Special
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supervision and mentorship of Dr. Zitnik, the Associate will: 1) Explore and learn about state-of-the-art techniques for constructing, maintaining, and contextualizing biomedical datasets by reviewing recent
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) is a community of Information Technology professionals committed to understanding our users and devoted to making it easier for faculty, students, and staff to teach, research, learn, and work through