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adapt to ever changing needs Preferred Qualifications: ● Research experience in natural language processing on biomedical and/or clinical texts, computer vision on medical images, causal inference
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inferences from observational datasets ● Familiarity with urban ecology, aquatic plant ecology or watershed biogeochemical processes ● Proficiency with GIS About the Department Ecology, Evolution, and
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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organizational, quantitative analysis and writing skills are necessary. Candidates with a strong background in molecular virology, next-generation sequencing, Bayesian analysis, phylogenetic analysis, statistical