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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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scientists—on projects that bridge methods, policy, and practice. Position Description: This role will involve intensive analysis of claims data and related large administrative datasets to support policy
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the intersection of programming languages and artificial intelligence (PL+AI), in particular verification and large language models. Our main goal is to create a PL+AI system that is the best at verified program
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sophistication, including strong statistical skills and comfort with large-scale or complex data. Experience with computational text analysis, such as NLP methods, historical text processing, topic modeling
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Director of LISH (Dr. Ramona Pop). The position involves conducting rigorous empirical research using field experiments, large-scale data analysis, and computational methods to advance our understanding
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working on public health, health services, and/or epidemiological research projects strongly preferred Strong quantitative background, experience working with large data sets and statistical and data
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data management and data cleaning and organization in large (N~100,000) datasets, including the Nurses Health Study cohorts, and the Health Professionals Follow-up Study. Data/Statistical Analysis
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, sociology, psychology, or closely related fields. Competitive applicants will have: Demonstrated quantitative sophistication, including strong statistical skills and comfort with large-scale or complex data
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transform visual information. We use large-scale electrophysiology and closed-loop visual experiments with macaque monkeys to discover the principles underlying cortical computation. We are seeking highly
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the Senior Director of Labs (Dr. Ramona Pop). The position involves conducting rigorous empirical research using field experiments, large-scale data analysis, and computational methods to advance our