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, applied statistics, Bayesian inference, and biostatistics, and its faculty are committed to excellent teaching in statistics and data science for students from across the School, the University, and in
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directionality and causal inference. This project instead builds on the structure of the central dogma, using genetic variation as an anchor for causal inference across molecular layers (genomics
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longitudinal methods, multilevel modeling, causal inference, Bayesian methods, computational modeling, and machine-learning approaches. Responsibilities include maintaining an active program of
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Ability to program in Python and develop automated simulation, data-processing, and inverse-identification workflows Familiarity with optimization, Bayesian inference, uncertainty quantification, or
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optimization, Bayesian inference, uncertainty quantification, or machine learning methods applied to engineering problems Ability to analyze and interpret experimental and simulation data, prepare peer
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data integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal
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sequential experimentation Bayesian optimization and active learning contextual bandits, reinforcement learning and online experimentation causal inference and treatment-effect heterogeneity
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trial design, and sequential experimentation Bayesian optimization and active learning contextual bandits, reinforcement learning and online experimentation causal inference and treatment-effect
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Link https://www.ubjobs.buffalo.edu/postings/64290 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting Detail Information Position
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monitoring, and the design of manipulation experiments, development of diagnosis frameworks (e.g., knowledge-guided machine learning, casual inference, and Bayesian neural networks), evaluation of