34 high-performance-computing-postdoc Postdoctoral research jobs at Harvard University
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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-relevant research related to aspects of the Medicare program, including payment policy, risk adjustment, and competition. Experience working with Medicare claims data, a deep understanding of econometrics
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to participate in the Harvard and Boston scientific community. Harvard University postdocs are offered competitive salaries and comprehensive benefits packages. Basic Qualifications We invite applications from
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chemistry, physics, and materials science. 2. Publish and present research findings in high-quality scientific journals and conferences. 3. Collaborate with faculty, researchers, and students
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, contingent upon work performance and continued funding to support the position. Standard Hours/Schedule: 35 hrs. per week | Monday - Friday | 9:00 am - 5:00 pm Visa Sponsorship Information: Harvard University
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manuscripts, participate in teaching and mentoring of lab members as needed, and otherwise contribute to the overall lab operations and collaborative environment. A strong sense of collaboration and high levels
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-relevant research related to aspects of the Medicare program, including payment policy, risk adjustment, and competition. Experience working with Medicare claims data, a deep understanding of econometrics
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Details Title Postdoctoral Research Positions in the GRASP (Gravity, Spacetime, and Particle Physics) Initiative at Harvard University School Faculty of Arts and Sciences Department/Area High-energy
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satisfactory performance. Contact Information Joseph Lavin Associate Director of Academic Affairs Department of Chemistry and Chemical Biology Harvard University 12 Oxford Street Cambridge MA 02138 Contact Email
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statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration