Research Assistant (PhD Student)

American Association of Colleges of Osteopathic Medicine•Bethesda, MD

13h•Remote

About The Position

AACOM is seeking a project-based Research Assistant to support a medical education research study examining predictors of clinical confidence and readiness among graduating osteopathic medical students. This temporary, part-time position is ideal for a doctoral student or recent PhD graduate with strong quantitative research skills and experience conducting advanced statistical analyses in R. The dataset has been fully assembled, research questions have been established, and the analytic framework has been developed. The selected candidate will execute the statistical analyses, prepare publication-quality tables and figures, and develop a manuscript suitable for submission to a peer-reviewed medical education journal. Our ideal candidate is someone who: Enjoys applying advanced statistical methods to educational research Has experience conducting exploratory and confirmatory factor analyses using R Produces clean, reproducible statistical code and clear technical documentation Writes publication-quality scientific manuscripts Works independently while collaborating effectively in a remote environment ABOUT AACOM The American Association of Colleges of Osteopathic Medicine, or AACOM, was founded in 1898 to lend support and assistance to the nation's osteopathic medical schools and to serve as a unifying voice for osteopathic medical education. The association is guided by its Board of Deans of member colleges of osteopathic medicine and various other member councils and committees. AACOM represents and advances the continuum of osteopathic medical education by: Supporting our member institutions as they educate the future physician workforce Increasing awareness of osteopathic medical education and osteopathic medicine Promoting excellence in medical education, policy, research, and service Fostering innovation and quality throughout medical education

Requirements

PhD in progress or completed in Statistics, Educational Research, Quantitative Methods, Biostatistics, Public Health, Psychology, or a related quantitative discipline
Demonstrated proficiency using R for statistical analysis
Experience conducting exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and multiple linear regression
Demonstrated ability to prepare publication-quality scientific manuscripts
Strong proficiency with R, including packages such as psych and lavaan
Strong quantitative reasoning and statistical interpretation skills
Excellent written communication and scientific writing abilities
Ability to organize and document reproducible analytic workflows
Ability to work independently, manage multiple project deadlines, and collaborate effectively in a fully remote environment
Interest in medical education or health professions education research

Nice To Haves

Prior first- or second-author publication in a peer-reviewed empirical journal
Experience with structural equation modeling
Experience analyzing survey data and large observational datasets
Familiarity with medical education or health professions education research

Responsibilities

Conduct exploratory factor analyses (EFA) using Principal Axis Factoring, oblimin rotation, and parallel analysis
Develop and compare confirmatory factor analysis (CFA) models for independent and dependent variable constructs
Perform multiple linear regression analyses examining three dependent variable subscales across seven independent variable clusters using both unadjusted and covariate-adjusted models
Evaluate model assumptions and interpret statistical findings
Produce publication-quality statistical tables and figures
Prepare a publication-ready manuscript for submission to a peer-reviewed medical education journal
Draft the Introduction, Methods, Results, and Discussion sections
Present statistical findings in a clear and scientifically rigorous manner
Incorporate feedback from project investigators throughout the manuscript development process
Develop clean, well-commented, reproducible R code
Maintain organized analytic documentation and workflows
Collaborate with the research team through regular virtual project meetings