Post-doctoral Fellow, School of Medicine / Family Medicine & Population Health

Summary

This interprofessional research position is designed as a transition to research
independence program for early career researchers interested in genetically-informed research. Training
will be available to develop skills in qualitative research, team science research approaches, genetic
analyses, and transitioning to careers inside and outside academia. The post-doctoral fellow will contribute
their effort to this NIH-funded project focused on measuring the degree to which participants are resistant
against substance use disorder and identifying genetic and environmental factors associated with this
outcome.

The post-doctoral fellow will collaborate with a multidisciplinary team, supporting data collection and
analysis of twins. The research will focus on analysis of a longitudinal sample of twins. An additional
portion of the project will include data collection and analysis of qualitative data. The post-doctoral fellow
will be responsible for supporting data management needs related to project analyses, leading a variety
of data analysis projects, conference presentation of results, manuscript publication in peer-reviewed
journals as well as non-traditional venues, and developing results dissemination materials to graduate level
students and the public related to study results.

Duties and Responsibilities:

• Data analysis of a longitudinal sample of twins and qualitative data.
o Generate population-level summary statistics (e.g., frequency tables, means, variances).
o Use regression, machine learning, and structural equation modeling to detail the role of
genetic and environmental factors on substance use resistance
o Use group concept mapping to identify resistance factors as detailed from study
participants

• Producing scientific products in peer- and non-peer reviewed venues to
summarize and disseminate study results.
o Draft and submit scientific manuscripts
o Generate blog posts and infographics summarizing scientific results from manuscripts.
o Include a specific task that falls under this responsibility.
o Support grant submissions using study results
o Disseminate study results at annual scientific conferences

• Data collection and management of a longitudinal sample of twins.
o Serve as a liaison between the primary investigators and the Mid-Atlantic Twin Registry
data collection team
o Receive and clean previously collected 6-wave longitudinal study and merge with newly
collected data of a seventh wave of the study for use in future data analysis.
o Use best practices to ensure data safety and study participant privacy.
o Use FAIR (Findable, Accessible, Interoperable, and Reusable) practices to ensure the
reusability of study data, protocols, analyses, and manuscripts

• Data collection and analysis of qualitative data.
o Manage and support research team activities in the collection of group concept mapping
data focused on substance use resistance.
o Use FAIR (Findable, Accessible, Interoperable, and Reusable) practices to ensure the
reusability of study data, protocols, analyses, and manuscripts.
o Use best practices to ensure data safety and study participant privacy.

• Managing research team activities.
o Supervise and mentor research team members as they generate blog posts and
infographics summarizing scientific results from manuscripts.
o Supervise and mentor research team members as they conduct group concept mapping.
o Review drafts of scientific writing and data analysis from team members.

Required Qualifications:

• Doctoral degree (PhD in a health-related discipline PhD such as Epidemiology, Public Health; or PhD
with a health-related focus such as health administration, health psychology, translational research,
or human genetics).
• Prior experience with the analysis of population-based substance use data
• Prior experience with structural equation modeling
• Excellent data analysis experience in SAS, R, SPSS, STATA, or equivalent statistical software
• Excellent oral, written, and interpersonal communication skills
• Demonstrated experience working in and fostering a diverse faculty, staff, and student environment
or commitment to do so as a staff member at VCU.

Preferred Qualifications:

• Experience in conducting qualitative data analysis projects
• Experience with the analysis of longitudinal data
• Experience with the analysis of twin data
• Experiential learning through lived experiences and/or professional service that informs worldviews
and/or perspectives about substance use resistance, to include race, age, ethnicity, gender,
sexuality, religion, and disability.

Position is open until filled.

This is a restricted position; continued employment is dependent upon project need, availability of funding, and performance.

Virginia Commonwealth University (VCU) School of Medicine is a premier academic medical center located in the heart of Richmond. Accounting for almost half of VCU’s sponsored research, the School of Medicine is internationally recognized for patient care and education. All full-time university staff are eligible for our generous benefits package that includes choices for health, vision, and dental coverage, life-insurance, short and long-term disability coverage, retirement planning, tax-deferred annuity and cash match programs, flexible spending accounts, tuition benefits, significant paid-time off, 12 paid holidays, and more. Explore our benefits further here: https://hr.vcu.edu/current-employees/benefits/university-and-academic-professional-benefits/

Virginia Commonwealth University is an equal opportunity, affirmative action university providing access to education and employment without regard to race, color, religion, national origin, age, sex, political affiliation, veteran status, genetic information, sexual orientation, gender identity, gender expression, or disability.

The School of Medicine continuously strives for our workplace and learning environment to reflect the demographic and social milieu of the communities we serve. All qualified applicants are encouraged to apply.