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the graduate curriculum, and social sciences scholarship across the school. Examples of topic areas include (but are NOT limited to): models for inference (e.g., SEM/CFA, Bayesian modeling, linear mixed effects
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currently consists of fourteen tenured/tenure-track faculty and nine full-time instructors. Current research areas of the faculty include survival and reliability analysis, Bayesian statistics, latent
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): applied optimization, Bayesian inference, big data analysis (especially as applied within astronomy or medical physics), computational statistics, data visualization, deep learning or statistical learning
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, and social sciences scholarship across the school. Examples of topic areas include (but are NOT limited to): models for inference (e.g., SEM/CFA, Bayesian modeling, linear mixed effects), data mining
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to statistical computing, Bayesian modeling, causal inference, clinical trials and analysis of complex large-scale data such as omics data, wearable tech, and electronic health record, with specific preference
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to statistical computing, Bayesian modeling, causal inference, clinical trials and analysis of complex large-scale data such as omics data, wearable tech, and electronic health record, with specific preference