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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
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evolving health trends Expertise in data management and statistical programming, particularly with SAS, SQL, STATA or R In-depth knowledge of research methodologies, systematic reviews, and syntheses Formal
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(SAS and SQL and occasionally STATA and R); • Demonstrated knowledge of research processes, systematic reviews, and syntheses; • Education/training and experience in quantitative research methods
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such as R or Python. The ideal candidate will be comfortable working with large geospatial datasets and interested in collaborating as part of a team on various CanN2ONet modelling initiatives. Experience
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planning. Coursework or research experience in road safety, traffic modelling, or transportation planning. Proficiency in working with open data sources for traffic and transit operations using R, Python
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., instrumental variables, propensity score matching, and treatment effects). Familiarity with one or more statistical software packages (e.g., R, Stata, Python) for data analysis. Research Aptitude: Demonstrated