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STATA, R, Python, Julia, and/or Matlab and ability to render accurate statistical analysis; as well as proficiency with LaTeX and Github. Familiarity with standard social science data sources, internet
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particularly encouraged. Advanced proficiency in the following coding languages: Proficiency in Coding Languages: R, Java, Python. Demonstrated experience with large and complex data sets. Demonstrated
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., forest biometry, forest science, natural resource assessment). Experience with open-source programming languages and software used in environmental data science with a preference for R. Proficiency with
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working with some languages, platforms, and environments to support interactive, computational research, such as Python, R, Jupyter, GitHub, and/or Unix Shell. Participation in The Carpentries or other data
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for phytoplankton in coastal ecosystems. Proficiency in R, Python, and code documentation/metadata creation. Experience with high-performance computing. Experience with time series and/or spatial analysis, and