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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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, regulated and exploited in cancer. The balance between method development, cancer biology and computational analysis will be shaped around your strengths and interests. Applicants from a physical-sciences or
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laboratory experience, such as: DNA/RNA extraction, PCR, cloning, virus production, ELISA, etc. Computational biology laboratory experience, such as: bulk- singl cell- or spatial-transcriptomic data analysis
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Details Title Pre-Doctoral Fellowship (Profs. Laibson/Choi/Beshears) School Faculty of Arts and Sciences Department/Area Economics Position Description Economics professors David Laibson (Harvard
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Details Title Pre-Doctoral Fellowship (Profs. Laibson/Choi/Beshears) School Faculty of Arts and Sciences Department/Area Economics Position Description Economics professors David Laibson (Harvard
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Details Title Pre-Doctoral Fellowship (Profs. Laibson/Choi/Beshears) School Faculty of Arts and Sciences Department/Area Economics Position Description Economics professors David Laibson (Harvard
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-026-01104-3. Preferred skills/knowledge Applications are invited from graduates in quantitative disciplines such as computer science, AI, and mathematics, but we also encourage applications from
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
or computer science (including course name, date taken, school, and the main textbook(s) used in the course); courses currently taking; date available to start work. Two references must send letter of recommendation to
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
, mathematics, statistics or computer science (including course name, date taken, school, and the main textbook(s) used in the course); courses currently taking; date available to start work. Two references must
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systems. The successful candidate should have a strong interest in mechanistic biology and in using experimental approaches to understand fundamental questions in cancer development. Computational