742 computational-physics "https:" "https:" "https:" "https:" "INRAE" positions at Harvard University
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Outside of Massachusetts . Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship
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submit a letter of interest and CV to Professor Archon Fung, Search Committee Chair, via: https://academicpositions.harvard.edu/postings/15422 . We will consider applications until the position is filled
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position in the Gozzi Lab at the Rowland Institute at Harvard (https://www.rowland.harvard.edu/). Our lab’s primary focus is on bacterial-encoded domesticated viruses, known as gene transfer agents
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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing
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submit the following materials through mathjobs.org: https://www.mathjobs.org/jobs/list/27619 All applications received by December 1, 2025 will receive full consideration. Please submit the following
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Center for Astrophysics at Harvard & Smithsonian: Postdoctoral Fellowships Deadline Month: Varies by program Description: The Center for Astrophysics (CfA) combines the resources and research
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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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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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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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–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