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Field
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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allotted towards studying for the EPPP and/or professional development (research, trainings, etc.) Towards the mid-point of their fellowship year, the postdoc will receive mentorship and guidance around the
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pursue independent research projects but also have the opportunity to work closely with students and postdocs supported by the faculty sponsor. The Scripps Research Fellows have full Principal Investigator
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 10 hours ago
, and reinforcement learning. Duties and Responsibilities A Postdoctoral Fellow (""postdoc"") is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop
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Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and
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) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty
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allotted towards studying for the EPPP and/or professional development (research, trainings, etc.) Towards the mid-point of their fellowship year, the postdoc will receive mentorship and guidance around the
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Computational Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal
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researchers at MIT. Program Details & Benefits • Each postdoc selected will be awarded a one-year funded appointment (possibly renewable for a second year) and receive research training, mentoring, and guidance
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data that are generated by human activity, including computational social science (e.g., algorithmic accountability and the interplay of data science with policy, law, and institutions), the economics