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Postdoctoral Fellow at Harvard in RL with Applications in Digital Interventions!
Job Description
Details
Title | Postdoctoral Fellow at Harvard in RL with Applications in Digital Interventions! |
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School | Faculty of Arts and Sciences |
Department/Area | Statistics |
Position 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 experimental design and reinforcement learning algorithms. We combine statistical methods with online reinforcement learning algorithms to provide inferential tools. The successful applicant will be expected to develop an innovative research program in sequential decision-making. Our lab is involved in a number of digital health studies in obesity, cardiac health, physical activity, mental illness, and substance abuse across the world. |
Basic Qualifications | Ph.D. in Statistics, Computer Science, Operations Research, or Electrical Engineering at time of appointment is required. The appointment will be for up to three years with annual renewal based on satisfactory performance and continued availability of funding. |
Additional Qualifications | |
Special Instructions | Send application materials (curriculum vitae, statement of research interests, and names and contact information for three references) to Research Administrator Jess Jackson (jessjackson@fas.harvard.edu ). |
Contact Information | Jessamyn Jackson Science and Engineering Complex 150 Western Ave, Sci&Eng, #2.401 Allston, MA 02134 |
Contact Email | jessjackson@fas.harvard.edu |
Equal Opportunity Employer | We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law. |
Minimum Number of References Required | |
Maximum Number of References Allowed | |
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