Many of the strongest observational research approaches available for program or policy evaluation (e.g., difference-in-differences) do not account sufficiently for treatment effect heterogeneity with respect to time. To the extent these differences are ignored, treatment effect estimates can be biased, leading promising treatments to be overlooked or allowing harmful practices to be sustained. Our team is conducting a Monte Carlo simulation study to identify and refine best practices for obtaining unbiased treatment effect estimates when treatment effects vary with time.

We are looking for a full time (40 hours/week) Postdoctoral Research Fellow to lead the programming of a simulation analysis focused on heterogeneity of treatment effects with time and contribute to interpreting results, preparing manuscripts, and disseminating programs to other analysts. This project is supported with funding by a 1-year grant from NIH/NIA (PI: Melissa Garrido, PhD); there is a possibility for renewal based on funding and performance. The Postdoctoral Research Fellow will have the opportunity to develop their own papers and grants on these topics and be encouraged to engage in professional development. They will also have the opportunity to engage in the development of high-priority policy, planning, and management initiatives and quantitative program evaluations with strong potential to improve the quality and efficiency of Veterans Affairs benefits through the Partnered Evidence-based Policy Resource Center.  

Applicants should be detail oriented, have training in econometrics and observational data analysis and strong Stata/Mata programming skills, and be interested in a research career. A PhD in statistics, economics, quantitative social sciences, or related fields is required.

Essential Functions

1. Statistical programming (60%)
2. Manuscript writing and formatting (20%)
3. Professional development and independently-led work (20%)

QUALIFICATIONS:

• Excellent Stata programming skills
• A history of scientific publications is desirable
• Self-motivated and committed to methodological research
• High level of professionalism and attention to detail
• Doctoral degree in statistics, economics, quantitative social sciences, or related field
• Familiarity with Monte Carlo simulation techniques and difference-in-differences and inverse probability of treatment weighting methods is preferred
• Familiarity with health policy is a plus
• Ability to manage time well

DO NOT APPLY THROUGH THE BU WEBSITE:

TO APPLY:

Please email a cover letter, CV, and two-page research statement to garrido@bu.edu.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We are a VEVRAA Federal Contractor.

Required Skills Required Experience