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Develop new statistical models to jointly analyze multi-species data from a broad range of data sources. Develop reproducible code (and potentially an R package) to apply this method to the data. Analyze
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desirable. Proficient in Python, R, and ML libraries such as PyTorch or TensorFlow. Strong communication and collaboration skills; ability to work independently and as part of a team. Willingness to respect
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author publication(s) in journals relevant in your field and/or shared as preprints Strong statistical foundation and expertise in R or python for data analysis Fluent in written and spoken English and
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reports from a large clinical dataset Using statistical analysis packages (e.g., SAS, R, SQL) to analyze large healthcare administrative datasets Participating in quantitative study design and
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-motivated and independent work skills Ability to work as part of a team. Preference will be given to applicants with intermediate or advanced computer skills in the following software packages: R, Stata
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to work as part of a team. Preference will be given to applicants with intermediate or advanced computer skills in the following software packages: R, Stata or SAS (quantitative data analysis software), MS
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research, large-scale population survey data preferred - Experience with SPSS required, comfortable using R, Mplus, SAS, or Stata considered an asset - Experience with community-engaged projects preferred
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R, Mplus, SAS, or Stata considered an asset Experience with community-engaged projects preferred Demonstrated understanding of and/or ability to work with marginalized youth, including immigrants and
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). Minimum of two years related experience. • Demonstrated skills in data management and programming using statistical packages (SAS and SQL and occasionally STATA and R); • Demonstrated knowledge
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statistics, data management). Comfort handling large and diverse datasets. Strong coding skills (R and/or Python), with experience using a high-performance computing platform (e.g., Digital Research Alliance