152 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" Fellowship positions at Harvard University
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or qualification, field of scholarship, and accomplishments in the field. Create a Job Match for Similar Jobs About Harvard University Harvard University is devoted to excellence in teaching, learning, and research
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academic calendar, looking at 2026-2027 dates: https://registrar.fas.harvard.edu/calendars#tenyear). Applicants may consider an early September start date, or a late January start date, for shorter
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PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective
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development. More information about the lab and specific research areas can be found at https://sites.harvard.edu/zheng/. We welcome applications from recent chemistry or chemical biology PhD graduates with
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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
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applications for a Postdoctoral Fellow with Professor Pragya Sur. Professor Sur’s lab focuses on research in high-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI
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common CNAs found in breast cancer (https://pubmed.ncbi.nlm.nih.gov/39567747/). Several lines of evidence suggest that these CNAs increase cell fitness and that cells carrying these CNAs represent
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. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Harvard Academic Workers Union
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at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective bargaining and matters affecting your
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knowledge of Ancient Maya epigraphy. Experience in a research library, archive, special collection, museum, or comparable environment. Strong computer skills, including experience using relational databases