Research Assistant, PhD Student

This is a fully remote position, open to applicants in Maryland.

📋 Description

• Conduct exploratory factor analyses (EFA) utilizing Principal Axis Factoring, oblimin rotation, and parallel analysis.

• Develop and evaluate confirmatory factor analysis (CFA) models for both independent and dependent variable constructs.

• Execute multiple linear regression analyses to investigate three dependent variable subscales across seven independent variable clusters, applying both unadjusted and covariate-adjusted models.

• Assess model assumptions and interpret statistical outcomes.

• Create publication-quality statistical tables and figures.

• Prepare a manuscript that is ready for submission to a peer-reviewed medical education journal.

• Write the Introduction, Methods, Results, and Discussion sections.

• Present statistical findings in a clear and scientifically rigorous manner.

• Integrate feedback from project investigators throughout the manuscript development process.

• Develop clean, well-commented, and reproducible R code.

• Maintain organized analytic documentation and workflows.

• Collaborate with the research team through regular virtual project meetings.

⛳️ Requirements

• PhD in progress or completed in Statistics, Educational Research, Quantitative Methods, Biostatistics, Public Health, Psychology, or a related quantitative discipline.

• Proven proficiency in utilizing R for statistical analysis.

• Experience in conducting exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and multiple linear regression.

• Demonstrated capability to prepare publication-quality scientific manuscripts.

• Strong proficiency in R, including familiarity with packages such as psych and lavaan.

• Excellent quantitative reasoning and skills in statistical interpretation.

• Outstanding written communication and scientific writing skills.

• Ability to organize and document reproducible analytic workflows.

• Capability to work independently, manage multiple project deadlines, and collaborate effectively in a fully remote setting.

• Interest in medical education or research in health professions education.

• Previous first- or second-author publication in a peer-reviewed empirical journal (Preferred).

• Experience with structural equation modeling (Preferred).

• Experience in analyzing survey data and large observational datasets (Preferred).

• Familiarity with research in medical education or health professions education (Preferred).

🏝️ Benefits

• This position is not benefits eligible.