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real-world databases, especially claims and EHR databases. Prior experience with cloud computing. Strong programming skills using at least one of the following programming languages; SAS, R, SQL
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following programming languages; SAS, R, SQL, or Python. Prior publication of peer-reviewed manuscripts in reputable journals. Strong written and interpersonal communication skills. Ability to work
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species responses to climate change and human caused landscape alteration. Use analytical tools (Geneious and R software, or similar programs) to analyze and summarize genetic data, prepare presentations
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; modeling bumble bee species responses to climate change and human caused landscape alteration. Use analytical tools (Geneious and R software, or similar programs) to analyze and summarize genetic data
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foliar fungicide studies in soybeans. Develop and apply spatial models to analyze the distribution and spread of soybean pathogens in Ohio, leveraging open-access tools like R and QGIS to visualize and
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of population and community modeling or coding. The Post Doctoral Scholar should have demonstrated ability to analyze population or community datasets using statistical software, such as R, data management skills
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one of the following areas: Computer Science, Computer Engineering, or other similar disciplines with strong quantitative background. Proficiency in at least one programming language, such as R, C
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related quantitative field. • Strong data analytic and programming skills in Python and/or R. • Proficiency in Unix/Linux systems. • Excellent writing and communication
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to have strong data analytic and programming skills in Python and/or R, as well as proficiency in Unix/Linux system. Review of applications will begin immediately and will continue until the position is
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. Proficiency in R (or Python or Stata), including experience with data management, spatial analysis, geocomputation. Experience working with large, complex datasets, including Consumer Reference Datasets (CRDs