534 computational-physics "https:" "https:" "https:" "https:" "INRAE" uni jobs at Harvard University
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who connects people, information, and processes across roles. This includes synthesizing updates, maintaining program documentation, identifying and implementing process improvements, and providing
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Classroom Use Salesforce to track and manage participant enrollment and cancellations, and other program-related data Coordinate, process, and track program purchases and other expenses Staff the program
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of Information Technology, providing state of the art computational expertise to the CBAR. The System Administrator will collaborate with other members of the IT Infrastructure Team, maintaining and administering Linux
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opportunity to shape the future of medicine. Job Description The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for a
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positive impact on the education sector. The Director oversees the program design process—including instructional design and course development—and provides leadership in identifying and adopting new
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. This role sits at the intersection of neuroscience innovation, industry partnership, and venture development. The successful candidate will serve as both strategic program architect and scientific driver
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. IIHP administers two academic programs: the Harvard PhD Program in Health Policy and the Harvard College Secondary Field in Global Health and Health Policy. The PhD program draws on faculty from six
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computer use for extended periods of time. Lifting (approximately 20 to 30 pounds), bending, and other physical exertion. Qualifications Basic Qualifications: Bachelor’s degree or equivalent work experience
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(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 (the Harvard Kenneth C
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–AWS Impact Computing Alliance. This role is designed for an engineer who thrives in research settings and enjoys translating scientific goals into robust, efficient, and reproducible AI/ML systems