212 distributed-computing-"St"-"University-of-St"-"St" positions at Harvard University
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Inference , Causal Inference , Data Science , Engineering , Life Science , Machine Learning , Management , Science , Social Science , Statistics Computer Science / All areas Economics Mathematical Physics
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and Sciences (FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs
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and Sciences (FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs
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credited to the Yang Visiting Scholars Program in World Christianity at Harvard Divinity School. Eligibility Positions are open to early career and senior scholars with doctorates in the fields of religion
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(strongly preferred) Interest in applying to a quantitative PhD program and pursuing an academic career (strongly preferred) We prefer research assistants who want to become professional economists, but we’re
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@seas.harvard.edu . Applications will be reviewed on a rolling basis. Basic Qualifications A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment. Additional Qualifications
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rolling basis. The position will remain open until filled. Basic Qualifications A Ph.D. in Mathematics, Applied Mathematics, Computer Science, or a related field, by the start of the appointment. Additional
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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for Science Information Analysis (CSIA) Public Relations Publications Social Media Programs Programs Support for Research Initiatives Grants-in-Aid for Scientific Research Topic-Setting Program to Advance
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be