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genetic sequences, from outbreaks and epidemics. These data could be at the household or population level, and the methods development can include causal inference, model diagnostics, estimation
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programming language R as well as experience with evaluation design, survey sampling, causal inference, small area estimation, and/or statistical modelling. An advanced degree in statistics, biostatistics
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with statistical modeling (ideally Bayesian statistics) • Proficiency in Fortran, R, Python, Matlab, or ideally other common languages (e.g., C/C++) Strong computational skills Strong oral and written
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methods, Bayesian statistics, and/or an interest in applied empirical problems. We are particularly interested in candidates with expertise in applications of artificial intelligence in marketing