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Instructional Track Program Director (Open Rank) - 21SAS-210530-ECO- FY27-1005

University of Rochester

Rochester, NYJob$100–140K/yrSeen 3w agoSeen in employer's feed 3 days ago

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At a glance

Compensation
$100–140K/yr
Location
Rochester, NY
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Doctorate

Job overview

The University of Rochester seeks an instructional‑track faculty member at the Assistant, Associate, or Full Professor level to launch, lead, and administer a new in‑person MS in Quantitative Social Science, teaching master’s courses, advising students, and managing program administration.

Skills & qualifications

RequiredNice to have

Skills

Quantitative MethodsStatistical MethodsComputational MethodsData‑Analytic MethodsGraduate TeachingCurriculum DevelopmentRelationship Building

Qualifications

PhD in Political Science, Economics, Statistics, Computer Science, Data Science or Related FieldGraduate Teaching ExperienceCurriculum Development ExperienceExperience Applying Quantitative Methods to Political Science or Economics

Full job description

University of Rochester: Office of the Provost: Academic Center: School of Arts & Sciences: Political Science

Salary Range or Pay Grade

$100,000 - $140,000

Description

The University of Rochester’s Goergen Institute for Data Science and Artificial Intelligence (GIDS-AI), Department of Economics, and Department of Political Science invite applications for an instructional-track faculty position at the Assistant, Associate, or Full Professor rank to help launch, lead, and administer a new in-person MS in Quantitative Social Science degree program. This MS program is a new joint initiative of the three units aimed at providing rigorous training in statistical, computational, and data-analytic methods for addressing social science problems. We seek candidates with expertise in quantitative methods and their application to substantive problems in the social sciences. The anticipated start date for the position is July 1, 2027.

Responsibilities:

  • Develop and teach courses for master’s-level students

  • Build relationships with external organizations and industry partners to develop capstone projects and supervise those projects

  • Advise students in the MS program

  • Manage the day-to-day administration of the MS program, including admissions and enrollment, curriculum development and oversight, marketing, and coordination with related administrative functions across the University.

Qualifications

Applicants must have a PhD in political science, economics, statistics, computer science, data science, or a related field. Experience with graduate teaching and curriculum development is preferred. Preference will be given to candidates with experience applying quantitative methods to political science or economics through academic research, teaching, and/or industry experience.

Application Instructions

Interested applicants should submit a cover letter, CV, teaching statement, and the names and contact information for two references. Letters of recommendation are not required at the application stage, but may be requested at a later date.

Questions concerning this position may be directed to Paulo Barelli ([email protected]) , Professor and Chair of the Economics Department, Mujdat Cetin ([email protected]) , Professor and Director of GIDS-AI, or David Primo ([email protected]) , Professor and Chair of the Political Science Department. Applications received by December 15, 2026, will be given priority consideration. Applications received after that date will be considered until the position is filled.

Equal Employment Opportunity Statement

EOE, including disability/protected veterans

The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion/creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Classes). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates for all persons consistent with our values and based on applicable law.

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