The University of Minnesota is seeking a post-doctoral associate, in a position jointly sponsored by the Minnesota Population Center (MPC, www.pop.umn.edu) and the Division of Epidemiology and Community Health in the School of Public Health. This position is on an exciting new social epidemiology research project examining how housing policy and neighborhood context influence the health and social mobility of low-income adolescents and their parents. The ideal candidate will have background in social determinants of health and in applying sophisticated quantitative analysis to investigate the relationships among social policy, neighborhoods, socioeconomic status, and/or health. The candidate will report to project director Dr. Theresa Osypuk, Associate Professor of Epidemiology and Community Health, and MPC faculty member.
Housed in the University of Minnesota’s Institute for Social Research and Data Innovation (ISRDI), the MPC is a hub for interdisciplinary population research. Its members include more than 100 faculty, research staff, and student affiliates from two dozen academic units across ten colleges in the University. Established in 2000 and funded by the National Institutes of Health, MPC cultivates innovative population research by providing a stimulating environment for interdisciplinary exchange, a vibrant and growing population training program, and generous research support services designed to develop and nurture promising areas of new population research. Research and training at the MPC are characterized by a focus on four core substantive areas: population health and health systems; population mobility and spatial demography; reproductive and sexual health; and work, family, and time. Affiliates of the MPC benefit from co-location with the renowned IPUMS data infrastructure projects, the University of Minnesota’s Life Course Center, and the Minnesota Research Data Center (which is part of the Federal Statistical Research Data Center Network).
The School of Public Health is consistently ranked in the top 10 of all Schools of Public Health in the United States, and is among the very highest in research productivity. The Division of Epidemiology and Community Health (http://www.sph.umn.edu/epi) provides a rich and collaborative environment for the investigation of the etiology, distribution, and prevention of disease integrating both clinical/biological and social/behavioral perspectives and methods. The Division offers graduate training programs leading to the MPH, MS and PhD degrees, and has active pre- and post-doctoral training. It has 45 primary faculty members who bring in over $30 million annually in sponsored research grants, and an additional 80 adjunct faculty. Major assets of the Division of Epidemiology and Community Health include access to several ongoing community-based intervention studies and large prospective cohort studies.
In this position, the postdoctoral associate will be constructing residential histories; linking individual and family data to diverse neighborhood contextual measures over time; developing statistical code; merging and managing multilevel data sets; coding and documenting variable construction; authoring and co-authoring manuscripts, conference papers and presentations, and scientific reports; conducting literature reviews; ensuring quality control of data and statistical code; and collaborating among a team of quantitative analysts and investigators to pursue project aims. Proficiency in a restricted-use data environment will be central. In addition, the postdoctoral associate will be expected to carry out substantive research in collaboration with Dr. Osypuk and other project collaborators, related to the project aims and data, the products of which will be expected to be presented at academic conferences and submitted for publication in peer-reviewed journals. The post-doctoral associate will be embedded within rich intellectual research environments, will receive professional development opportunities, and will be mentored to facilitate transition to independent research careers by emphasizing the acquisition of analytic, writing, and other research skills. This post-doctoral appointment is for one year with possible renewal for up to one additional year depending upon funding and performance.
Minimum qualifications include 1) a doctoral degree in epidemiology or related quantitative field; 2) strong quantitative analysis skills, and at least 3 years of statistical programming experience, including expertise in statistical software (SAS, Stata, and/or R); 3) excellent data management skills for manipulating large databases and complex survey designs; 4) strong verbal and written skills in English; 5) experience fostering an inclusive environment and appreciative of differences in the workplace. Additionally, the candidate must have or obtain Special Sworn Status with the US Census Bureau, within 3 months of employment, in order to work in the Research Data Center on the University of Minnesota campus. This will involve a background check, and either US citizenship or a candidate who has resided within the US for the past 2-3 years. We expect that if the chosen candidate does not have SSS when accepting the position that they will apply for SSS within 1 week of accepting the position.
Preferred qualifications also include substantive knowledge of and experience examining socioeconomic status, and other social determinants of health, with health outcomes.
Please apply using the University of Minnesota’s online employment system humanresources.umn.edu/jobs and search job opening ID 324064. Application requirements include a curriculum vitae, names and addresses of three references, a writing sample (e.g. first-authored article), and a cover letter describing expertise and qualifications, research and scholarship interests, and career plans. Please include in the cover letter when you are available to start and clearly describe your expertise and experience related to this project. Applications will be reviewed on a rolling basis, and the position will remain open until filled. Questions concerning the application process may be addressed to Mia Riza, HR Generalist, at firstname.lastname@example.org.
Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.