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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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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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role in advancing our mission to develop next-generation digital twin frameworks that integrate physics-based modeling, data-driven inference, and real-time monitoring to support robust lifecycle
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