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, medical image processing, metabolomics data analysis, survival analysis, causal inference, statistical methods of health surveys, high dimensional inference, longitudinal data analysis, and clinical trials
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. Experience leading investigations linking simulations to observational data. Experience with statistical characterization of data, preferably within a Bayesian framework. Job Description: A Post-doctoral
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intervention studies, medical image processing, metabolomics data analysis, survival analysis, causal inference, statistical methods of health surveys, high-dimensional inference, longitudinal data analysis, and
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(LLMs) and other foundation models. Development and application of causal inference and discovery methods, particularly causal AI approaches for clinical trial emulation. Special Instructions
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, medical image processing, metabolomics data analysis, survival analysis, causal inference, statistical methods of health surveys, high dimensional inference, longitudinal data analysis, and clinical trials
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, particularly within the context of QMRA. Strong proficiency in R/RStudio (modeling, simulation, inferential statistics, etc.). Familiarity with Bayesian statistics. Foundational knowledge of general microbiology
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postdoctoral associate positions, starting immediately. Dr. Liu has extensive experience in big data analytics, systems biology, probabilistic graphical models, causal inference and machine learning. Dr. Liu's
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intervention studies, medical image processing, metabolomics data analysis, survival analysis, causal inference, statistical methods of health surveys, high-dimensional inference, longitudinal data analysis, and