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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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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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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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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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, 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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knowledge suitable for processing raw data for analysis (e.g., text manipulation); modern methods in machine learning, AI, including use of LLMs. One or more computational environments for statistical
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, Kinesiology, Movement Science, Physiology, Biomedical Engineering or a related field. Additional Qualifications A strong background in statistics, as well as previous experience in human subjects studies with
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equivalent degree in computer science, statistics, economics, management science, information systems, operations, or other related quantitative and/or social science domains. All degree requirements must be
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economics, mathematics, quantitative sciences, or business-related field required. Statistical/programming experience and/or applied experience with Python, R, Stata or other languages Additional
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analysis, organizational skills, and strong interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions