PHI Postdoctoral Research Associate Youth-Nex

Swcenter; Charlottesville (VA); On-site; USD 60,000 - 65,000; Full time

Job summary

A leading research center is seeking a Postdoctoral Research Associate to join their Preventive Interventions Team. The role involves analyzing data, conducting advanced statistical analyses, and contributing to research on youth development. Candidates will receive mentorship in precision health and statistical methods, with opportunities to publish and present findings. Ideal for early-career researchers with a strong background in mental health and statistical analysis.

Qualifications

• Doctoral degree required.
• Experience with large datasets and statistical methods.

Responsibilities

• Analyze data from various mental health programs.
• Lead and co-author papers for peer-reviewed journals.
• Support grant submissions and project management.

Skills

Mental Health

Statistical Expertise

Research-Practice Partnerships

Education

Ph.D. in a research-oriented field

Tools

Stata

R

SPSS

Job description

The University of Virginia School of Education and Human Development's Center to Promote Effective Youth Development ( Youth-Nex ) is seeking highly qualified applicants for a one-year Postdoctoral Research Associate position, with the possibility of extension based on an annual basis dependent upon satisfactory performance and the availability of funding. This position is part of the Preventive Interventions Team: Collaborative Research on Engagement and Wellbeing (PIT-CREW), which conducts research related to promoting effective youth development, intervention, and programming, including preventing behavioral and mental health problems in schools.

This position is funded by the UVA Precision Health Initiative (PHI), with a focus on using the tools of precision health to improve outcomes and reduce disparities for communities and populations. Candidates will receive mentorship and training in precision health, including advanced statistical methods focused on predictive modeling in relation to response to preventive interventions, decision support to implement mental health interventions, longitudinal data analysis, machine learning/NLP/AI, integrative data analysis, and related grant writing. This candidate would work under the mentorship of Dr. Catherine Bradshaw , and collaborate on methodologically intensive studies with Drs. Lex Budavari and Ali Ünlü .

Responsibilities include:

• Analyzing data collected through the implementation of the Coping Power Rural Program , Double Check Online program, Integrative Data Analysis Projects, the mental health screening of students, and related evidence-based programs within the PIT CREW and National Center for Rural School Mental Health .
  
• Run advanced quantitative analyses using software such as Stata, R, Mplus, HLM, and/or SPSS.
  
• Generate research questions for analysis utilizing quantitative data collected from prior trials of prevention programs and frameworks like PBIS, Double Check, Coping Power, MTSS-B, and the R-CITY model.
  
• Lead and co-author papers for submission to peer-reviewed journals.
  
• Communicate research findings at key conferences (e.g., Society for Prevention Research, Society for Research in Child Development, American Association for Public Health, Society for Research on Adolescence, etc.).
  
• Contribute to submission of federal and private grant proposals including to funders (e.g., current and prior funders include Institute of Education Sciences, National Institutes of Health, William T. Grant Foundation, etc.).
  
• Support the data use agreements for ongoing projects, which may include research activities related to obtaining, modifying, and continuing institutional review board approval (IRB), communicating with local district and collaborating sites and school partners.
  
• Contribute to the intellectual environment of the broader PIT-CREW team and Precision Health Initiative by keeping current on recent scientific studies and relevant advanced quantitative methods, and regularly attending and presenting findings at lab meetings.
  
• Providing near-peer-mentorship to PhD students and other early-career-scholars on the research team.
  
• Support the team with data cleaning, project management, and grant submission tasks as needed.
  
• Other tasks include various writing and content creation (e.g., research briefs to research and school partners), technical assistance, and presentations.
  

Knowledge/Skills/Abilities:

• Content expertise in some of the following areas: mental health, screening, rural and/or urban K-12 school settings, school climate, multi-tiered systems of support, positive behavior support, social emotional learning, implementation science, school-based intervention, teacher professional development and coaching, and implementation/coaching supports.
  
• Statistical expertise: expertise in two or more of the following areas ML/NLP, integrative data analysis, SEM, latent class analysis, GGM, longitudinal data analysis, multilevel analysis.
  
• Methods expertise in one or more of the following areas: Research-practice partnerships; conducting applied research in school settings; randomized controlled trials.
  
• Administrative expertise: Proficient with Box, Google Suite, Microsoft Suite (Word, Excel, PowerPoint, Outlook, Teams), Zoom, and ability to learn new statistical software quickly and introduce new useful applications and platforms to the team.
  

Minimum Requirements
Education: Doctoral degree

Preferred Qualifications

Education: An earned Ph.D. in a research-oriented field, such as Research/Statistics/Evaluation, Public Health, Data Science, Prevention Science, Clinical/School Psychology, Education, Psychology, or a related field is required by the start date of the position.

Experience: The ideal candidate is an early-career researcher with prior experience working with large datasets and cutting-edge statistical methods, and some knowledge or interest in mental / behavioral health prevention in schools, strategies to identify students in need of mental health services, and evidence-based programs.

Anticipated Hiring Range: $60,000-$65,000 (commensurate with qualifications). For more information on the benefits available to postdoctoral associates at UVA, visit postdoc.virginia.edu and https://hr.virginia.edu/benefits .

Application Instructions: Apply Now . Internal applicants must apply through their UVA Workday profile, search Find Jobs and then R0072313. Complete an application online and include the following documents:

• Cover letter (addressed to Catherine Bradshaw)
  
• CV/resume
  
• Two publications/writing samples
  
• Statement of research interests
  
• Contact information for three references who can comment on your scholarly accomplishments and promise.
  

All documents can be loaded into the resume submission field, multiple documents can be submitted into this one field. Incomplete applications will not be considered.

For questions about the position, please contact Youth-Nex . For questions about the application process, please contact Margaret Weeks , Academic Recruiter. Before a formal offer of employment is extended, the selected candidate will undergo a background check per university policy.

Research Associates are appointed annually, and continuation is dependent upon satisfactory performance and the availability of funding. Review of applications will begin 10 days after posting and will remain open until filled.

Physical Demands

This is primarily a sedentary job involving extensive use of desktop computers. The job occasionally requires local and regional travel to attend in-person meetings with research team members, and walking some distance to attend meetings, and programs.

The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physicians Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experience. We are equal opportunity employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.