Postdoctoral Research Associate in Disparities in Heart Failure PH-288 Brown University

  • Brown University
  • Providence, Rhode Island
  • Full Time

The Department of Epidemiology at the Brown University School of Public Health invites applications for a full-time Postdoctoral Research Associate position that will be supported by an NIH-funded R01 grant titled, Racial/Ethnic Disparities in Heart Failure: A Cross-Cohort Collaboration (MPIs: Drs. Charles Eaton, Chanelle Howe and Norrina Allen). This grant will evaluate the magnitude and potential causes of racial/ethnic and sex disparities in incident heart failure and its subtypes and their prognosis. The impact of hypothetical lifestyle and clinical risk factor interventions on reducing racial/ethnic disparities in developing heart failure will also be evaluated. In addition, unsupervised machine learning phenomapping techniques will be used to evaluate subtypes of heart failure and their prognosis, including models stratified by race/ethnicity.

The Postdoctoral Research Associate will be affiliated with the Center for Epidemiologic Research at Brown and supervised by Dr. Chanelle Howe. The Postdoctoral Research Associate will receive mentorship and training in conducting heart failure disparities research and causal inference methods. The Postdoctoral Research Associate will complete data analyses as well as lead or assist in the publication and presentation of study findings. The Postdoctoral Research Associate will also generate consortium-related reports. A doctoral degree in Epidemiology, Biostatistics, or a related quantitative field as well as knowledge of SAS or R is required for the position. The position is for a minimum term of one-year, with the expectation of renewal.

Required and preferred qualifications:

  • A doctoral degree in Epidemiology, Biostatistics, or a related quantitative field is required
  • Knowledge of SAS or R is required
  • Experience analyzing complex cohort data is preferred
  • Experience with data harmonization is preferred
  • Experience with conducting health disparities research is preferred
  • Experience with the application of causal inference methods is preferred
  • Excellent communication (i.e., verbal and written) and collaborative skills are preferred

The preferred start date for the position is January 1, 2022; however an earlier or later start date may be able to be negotiated. Brown University is committed to fostering a diverse and inclusive academic global community; as an EEO/AA employer, Brown considers applicants for employment without regard to, and does not discriminate on the basis of, gender, sex, sexual orientation, gender identity, national origin, age, race, protected veteran status, disability, or any other legally protected status. Review of applications will begin immediately and will continue until the position is filled or the search is closed. Candidates should apply with a cover letter (summarizing research experience, qualifications, and career goals, as well as addressing the applicant?s reasons for applying for the position and their commitment to diversity, equity and inclusion and how the applicant intends to show this commitment in future work through scholarship, teaching, mentoring, service, or community engagement), curriculum vitae, sample publication or equivalent, and 3 letters of recommendation. Candidates should apply online at: apply.interfolio.com/90484

Brown University provides equal opportunity and prohibits discrimination, harassment and retaliation based upon a person?s race, color, religion, sex, age, national or ethnic origin, disability, veteran status, sexual orientation, gender identity, gender expression, or any other characteristic protected under applicable law, in the administration of its policies, programs, and activities. The University recognizes and rewards individuals on the basis of qualifications and performance. The University maintains certain affirmative action programs in compliance with applicable law.

Job ID: 488008781
Originally Posted on: 8/4/2025

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