Temporary Health & Education Policy Research Associate: College of Nursing - UTK

University of Tennessee•Knoxville, TN

2d•Hybrid

About The Position

The College of Nursing (CON) at the University of Tennessee Knoxville seeks a health and education policy research associate to join an interdisciplinary research team. This role will contribute to an applied research project funded by the William T. Grant Foundation, focusing on school attendance, chronic absenteeism, and truancy using linked administrative data from Maryland’s education and juvenile justice systems. The project aims to identify middle and high schools that maintain strong attendance for underserved student populations while reducing punitive responses to absenteeism. This is a grant-funded position, contingent upon continued grant funding.

Requirements

Earned Master’s degree in economics, public health, public policy, or a related field.
Demonstrated experience with causal inference methods.
Advanced programming skills in Stata, Python, or R (at least one at an advanced level).
Experience working with large datasets and writing clean, well-documented code.
Excellent communication, organizational, interpersonal, and time-management skills.
Must be able to pass required background/security checks prior to data access.
Legally authorized to work in the United States on a full-time basis without need now or in the future for sponsorship for employment-based visa status.

Nice To Haves

Earned Doctorate
Interest in education research.
Interest in dissemination of research findings to practice audiences.

Responsibilities

Build, document, and maintain reproducible data pipelines (cleaning, merging, versioning).
Work with large administrative, multi-level, linked datasets; implement QA checks and validation.
Create codebooks and data documentation for internal use and publication.
Create matched samples of schools and students (e.g., propensity score matching, exact/coarsened exact matching, weighting).
Implement quasi-experimental methods such as dynamic difference-in-differences (DiD) and synthetic DiD using matched samples.
Produce publication-quality figures (event-study plots, balance diagnostics, distributions; maps if relevant).
Assist in drafting methods/results text, tables, and appendices as needed.