A Research Associate typically has more experience than a Research Assistant. Responsibilities can include the planning and design of research projects, conducting experiments, analyzing data, contributing to research publications or grant proposals, and collaborating with other researchers. Works in a variety of fields within science or the social sciences, in programs based at a university or research institution, or works on government or industry sponsored research projects. Conducts field or library research or recruits participants for a study; may also assist with legal research. These roles are often held by people with advanced degrees in their field of study with several years of experience in research or academia.
The successful candidate will lead and contribute to research that identifies risk factors and protective factors for a broad range of diseases and clinical outcomes using the National VA longitudinal EHR system. The Postdoctoral Research Associate will work within a highly collaborative, data-intensive environment integrating advanced AI/ML methodologies with rigorous epidemiologic study design. The Postdoctoral Research Associate will play a central role in translating complex EHR-derived data into clinically meaningful insights with direct relevance to Veteran health. Minimum Qualifications (Required): PhD in Epidemiology, Biostatistics, Public Health, or a closely related quantitative health discipline Strong background in longitudinal data analysis and observational study design Demonstrated experience working with electronic health record (EHR) data or other large administrative healthcare datasets Proficiency in statistical programming (e.g., R, SAS, Python, Stata) Track record of peer-reviewed publications
Additional Considerations:
The Postdoctoral Research Associate will be embedded within a multidisciplinary research team at UMass Lowell, with joint engagement at VA Bedford Healthcare System.
The environment emphasizes:
Integration of AI and epidemiology Large-scale, real-world longitudinal health data Translational research with direct clinical and public health impact Collaborative publication and grant development This position offers strong mentorship, access to national VA data resources, and opportunities for independent research development.
Preferred Qualifications:
Experience with causal inference methods (e.g., marginal structural models, target trial emulation, propensity score methods) Familiarity with machine learning methods applied to health data Experience working with VA data or other national healthcare systems Experience with high-performance or distributed computing environments Interest in interdisciplinary collaboration across computer science and clinical domains Special Instructions to
Applicants:
Only current UML Employees within the Grants & Contracts (MTA/GRACE) bargaining unit will be considered during the first 10 business days of the posting. All other candidates will be considered after that period. This position is full-time, benefited and Grace union in grade PD. Anticipated salary based on qualifications within range. Minimum $50,000, 25th quartile $56,500 and midpoint of $63,000. This position is contingent upon funding, and is for one year contingent on productivity, successful performance, and the availability of funding. This position may be extended based on these contingencies. Review of applications will begin immediately and continue until the position is filled; however, the posting may close when an adequate number of qualified applications is received. Please include a resume and cover letter with your application. Names and contact information of three references will be required during the application process.
