Assistant Professor in Political Science

Position description

Abo ut URI: The University of Rhode Island enrolls approximately 17,000 students across its graduate and undergraduate programs and is the State’s flagship public research university, as well as the land grant and sea grant university, for the state of Rhode Island. The main campus is located in the historic village of Kingston, and the Bay Campus is located in Narragansett. Both campuses are near major beaches in a beautiful coastal community. URI is just 30 minutes from Providence, RI and within easy reach of Newport, Boston, and New York City.
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POSITION SUMMARY:

The Department of Political Science at the University of Rhode Island invites applications for an Assistant Professor in Computational Social Science, starting in Fall 2026. We are seeking candidates with expertise in developing and applying cutting-edge computational and quantitative methods to the study of politics as well as a demonstrated ability to work across disciplines. Areas of methods focus may include, but are not limited to, AI, machine learning, deep learning, digital experimentation, natural language processing, network analysis, text analysis, big-data analytics, or system dynamics.

The successful candidate is expected to contribute to a new interdisciplinary Ph.D. program in Computational Social Science in the College of Arts & Sciences, with a 100% tenure home in the Department of Political Science.

We are seeking to attract a diverse pool of job applicants for this position. A key pillar of URI’s mission is to “inspire an enlightened community that is characterized by vibrant cultural diversity; that embraces difference; that is built upon a learning environment that fosters respect, understanding, and social justice; and that rejects prejudice and intolerance.” Our department seeks candidates whose principles align with that mission.

DUTIES AND RESPONSIBILITIES:

The successful candidate is expected to have strong skills in computational social science and a research program in any subfield of political science. Competitive candidates will have a scholarly track record with evidence of high-quality and computationally rigorous research informed by innovative quantitative, data-intensive, and computationally-intensive techniques.

The successful candidate will contribute to the new interdisciplinary Ph.D. program in Computational Social Science (CSS) within the College of Arts & Sciences. The candidate is expected to teach courses and advise and mentor students in the CSS Ph.D. program. This position will involve working closely with faculty across multiple social science and computational departments participating in the interdisciplinary CSS Ph.D. program.

The Computational Social Science Ph.D. program’s administrative home resides within the Political Science Department. The candidate will split teaching and service duties between the CSS Ph.D. program and the department’s other academic programs.
QUALIFICATIONS

REQUIRED:

1) Ph.D. in Political Science, Computational Social Science, or in a closely related discipline.

2) Expertise in one or more of the following areas: computational social science, big-data analytics, machine learning, AI, natural language processing, text analysis, or network analysis.

3) Demonstrated potential to excel in teaching advanced coursework on applications of innovative quantitative, data-intensive, or computationally-intensive techniques in the social sciences.

4) Demonstrated potential in advising and mentoring of students.

5) Evidence of political science research using advanced computational methods, with scholarly work commensurate with level of academic experience.

6) Demonstrated potential to develop and maintain an externally grant-funded research program relevant to Computational Social Science.

7) Demonstrated interpersonal communication skills.

8) Demonstrated experience working with diverse populations or in diverse environments.
PREFERRED:

1) Ability to teach undergraduate research methods courses and substantive political science courses.

2) Demonstrated experience or interest in interdisciplinary collaboration, particularly with statistics, computer science, or related fields.

3) Demonstrated interest in developing collaborative research and/or consulting to support the interdisciplinary nature of programs within the Department, College, and the University as a whole.

Application instructions

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