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Details Title Postdoctoral Fellow for Statistical Methods at the Intersection of Randomized Trials and Observational Studies School Harvard T.H. Chan School of Public Health Department/Area
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Details Title Postdoctoral Fellow for Statistical Methods in EHR-Based Studies School Harvard T.H. Chan School of Public Health Department/Area Position Description This is a postdoctoral position
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Details Title Postdoctoral Fellow in Statistics School Faculty of Arts and Sciences Department/Area Statistics Position Description The Department of Statistics invites applications for a
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, control theory, or a related field. Strong statistical understanding and a talent for data analysis and visualization using Matlab or Python are expected. Specific experience with experimental design
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target trial emulation in combination with advanced epidemiologic and statistical methods to draw inferences from longitudinal data to answer pressing outstanding questions related to the safety and
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Doctoral Students) at JSU, other HBUCs, and Harvard Chan School. 6. Severe as an instructor for epidemiologic methods and statistical analysis. 7. Mentor predoctoral trainees during their fellowship period 8
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, computer science, applied mathematics, or any related field. Candidates who have a strong analytical background in machine learning foundations, computer vision and perception, statistical learning theory
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
science, mathematics, statistics, or a related field; at least two years of specialized experience with quantitative data analysis, research methods, and/or social sciences research (which may include coursework
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learning foundations, computer vision and perception, statistical learning theory, reinforcement learning, control theory and decision science, and mathematical optimization are preferred. Candidates will
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statistical analyses • Running power calculations for randomized controlled trials using structural models • Assisting in the preparation of academic journal submissions and code and data for publication