Postdoctoral Research Associate (AY27-28) - DDSS in Princeton, New Jersey at Princeton University

Princeton University's Initiative for Data-Driven Social Science (DDSS) invites applications for the Postdoctoral Research Associate role. DDSS is part of Data and Intelligent Systems (DaIS) – Princeton’s new interdisciplinary hub for research and education in artificial intelligence, data science, and statistics. DDSS supports technical and methodological innovation in quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation of tools and public goods.

Responsibilities

This role's emphasis is on making substantive technical and methodological contributions that either directly or indirectly support DDSS projects or its mission. Candidates will be able to apply and further develop their technical skills in a dynamic research environment. The successful candidate will have the opportunity to work closely with our engineers and other research staff. Projects may include software package creation and maintenance, data engineering, development and/or implementation of advanced statistical methodologies, and supporting research on high performance and cloud computing.

The successful candidate will also be expected to offer 2-3 advanced technical or methodological workshops each semester, assist in organizing research-based events (e.g., speaker series, symposia, or reading groups), present their work at research methods and field-specific seminars, assist with DDSS and DaIS projects on occasion, and offer consultation to faculty, graduate students, and research staff on topics related to the candidate's area of expertise. Three days per week can be dedicated to independent research. Postdoctoral research associates work under the direct supervision of the DDSS Faculty Director and the Director for Research and Strategy.

Area of expertise is open, but preference will be given to candidates with expertise in one or more of the following: software package development and maintenance in R; record linkage/entity resolution; data privacy techniques; large data processing and high-performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge of C/C++ and/or at least one SQL dialect is preferred.

Review of applications will begin on December 1, 2026, and will continue until the position is filled. Postdoctoral appointments will be for one year, renewable annually based on funding and meeting all other requirements.

The appointment will be through DaIS. This position is subject to the University's background check policy. The work location for this position is in-person on campus at Princeton University; the position is not eligible for remote work.

This position is not eligible for sponsorship of an H-1B visa requiring consular processing; other visa sponsorships (including H-1B visas not requiring consular processing) may be available, as appropriate.

Applicants must have (or expect to have at time of appointment) a PhD in the social sciences, statistics, computer science, or related fields, and their interests must fall at the technical forefront of quantitative social science. Candidates should offer state-of-the-art technical or methodological skills, applying innovative techniques in the examination of substantive social science research questions. In addition to innovation, candidates will be evaluated on their potential to create public goods and their capacity for interdisciplinary engagement.

Please upload the following documentation:

1. Cover letter

2. C.V.

3. 1-2 page research statement, specifying research interests and example training workshops the candidate could offer

4. 1-2 research papers (please upload multiple research papers as one document)

5. Contact information for two references