How to Apply

To be considered for this position, applicants should submit the following materials: a cover letter, CV, one example of scholarly work, one example of a program that reflects the level of the applicant's coding skills, and two letters of recommendation. The review of applications will begin one week after this job opening is posted and will continue until the position is closed or filled. All application materials must be submitted via Interfolio: https://apply.interfolio.com/167162. All general inquiries and questions about the position can be submitted to [email protected].

All application materials must be submitted to the Interfolio link below. Do not use the "Apply Now" button above.

https://apply.interfolio.com/167162

The anticipated start date is September 1, 2025. The initial appointment is for one year, with an anticipated extension for an additional year contingent upon performance. The initial appointment and the extension are both contingent upon funding.

Job Summary

The Stone Center for Inequality Dynamics (CID) invites applications for a Postdoctoral Research Fellow. CID is a multidisciplinary research center that carries out cutting-edge substantive and methodological research on social and economic inequality and helps expand the scientific data infrastructure available to support the study of this topic. CID is housed at the Institute for Social Research, one of the world's largest social science research organizations.

The Postdoctoral Fellow (PF) will be a central contributor to the project "Workplace Income Distribution by Social Class in the United States Manufacturing Sector, 1967-2022," whose principal investigators are Dr. Tali Kristal (University of Haifa) and Dr. Pablo Mitnik (CID). The project is part of the larger project "Distributional Workplace Accounts" funded by the European Research Council and led by Dr. Kristal.

The position is an exciting opportunity to work with restricted and hard-to-access data related to the sources of class-based income inequality on cutting-edge research topics. We are seeking a candidate with strong quantitative skills and a background in stratification and inequality, economic sociology, organizational studies, or labor economics. We prefer someone highly proficient in Stata but will also consider those highly proficient in other statistical programming languages, such as R.

The PF will be granted time to pursue their own scholarly projects and will have an annual research budget to pay for the costs associated with presenting their research at conferences or other research expenses.

Responsibilities*

Under the guidance of the project's PIs, and in collaboration with the PIs and other team members, the PF's main responsibilities will include:

The construction of the project's analytic datasets, which will rely extensively on restricted data from the Census Bureau and will require, among other things, linking Census of Manufacturing data with data from the National Labor Relations Board and the Federal Mediation and Conciliation Service using name-and-address matching.
The production of the estimates required to describe the evolution of the labor share and the compensation gap between production and non-production workers at the establishment level over time.
The estimation of a variety of complex statistical models aimed at substantiating the explanatory account the project will offer.
Co-authoring papers for submission to top academic journals based on the research and contributing to the writing of a technical report for the Census Bureau summarizing main findings.

Required Qualifications*

Ph.D. degree in Sociology, Economics, Political Science, or a related field (awarded by the position's start date).
Knowledge and experience with advanced computational and statistical methods
Demonstrated success in designing and completing high-quality academic research projects
Experience with tools and techniques for strong data management, documentation, and other tools that support replicable research practices
High proficiency in at least one language or statistical package (e.g., Stata, R, Python)
Demonstrated interpersonal skills with excellent verbal and written English communication skills
Eligibility to work in a secure U.S. Census Bureau facility (U.S. citizen or three years of residence in the U.S. in the last five years).

Desired Qualifications*

Expertise programming in Stata
Experience working with big data
Expertise in class-based income inequality
Experience working in the Census Bureau's remote computer environment

Work Locations

Work location is expected to be onsite in Ann Arbor with flexibility for remote work within our overall Center policies.

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Additional Information

The salary is $70,000 plus benefits and travel funds.

The Institute for Social Research (ISR) at the University of Michigan seeks to create a community of respect and authentic collaboration by recruiting and retaining individuals that represent a variety of voices as a reflection of our commitment to serve the people of Michigan, to maintain the excellence of the university, and to ground our research in varied disciplines, perspectives, and ways of knowing and learning.

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.

Application Deadline

Institute for Social Research job openings are posted for a minimum of fourteen (14) calendar days. This opening may be removed from posting boards and filled any time after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.