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with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly desirable. Proficient in Python, R, and ML libraries
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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
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, STATA or R In-depth knowledge of research methodologies, systematic reviews, and syntheses Formal education/training in quantitative research methods and statistical analysis Excellent written and verbal
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and occasionally STATA and R); • Demonstrated knowledge of research processes, systematic reviews, and syntheses; • Education/training and experience in quantitative research methods, and