Instructional Professor (open rank) in Data Science

  • Professional
  • Chicago, IL
  • Posted 2 months ago
  • Expires on: June 30, 2021

University of Chicago
Department of Computer Science

The University of Chicago invites applications from Data Science educators for the position of Instructional Professor (open rank). The selected candidate will be appointed as Assistant Instructional Professor, Associate Instructional Professor, or Instructional Professor, depending on qualifications and educational background. The appointment will be for a term of up to five years, renewable. This is a career-track position with potential progression, competitive salary, and benefits.

The terms and conditions of employment for this position are covered by a collective bargaining agreement between the Service Employees International Union (SEIU) and the University.

The University of Chicago is initiating an ambitious plan for research and education in Data Science including new academic programs at the undergraduate level. The initiative is a collaboration among the Department of Computer Science, the Department of Statistics, and other units on campus. We particularly seek individuals who can help us fulfill our educational objectives in data science. Position responsibilities include teaching (average teaching load is two courses per quarter in the fall, winter and spring quarters), non-classroom instructional or service duties as needed, and professional development.

Appointments will be made in either department, jointly between Statistics and Computer Science, or jointly with another department in the University.

The Departments of Computer Science ( and Statistics ( at University of Chicago are home to a diverse community of educators and researchers focused on advancing the foundations of statistics and computing, and driving their most advanced applications. The larger data science community includes the Center for Data and Applied Computing, the Toyota Technological Institute at Chicago (TTIC), the Polsky Center for Entrepreneurship and Innovation, the Mansueto Institute for Urban Innovation and Argonne National Laboratory.

By the time of hire candidates must have completed all requirements for the PhD in statistics, computer science, or some field of mathematics or science where data science concepts play an important role. Prior college teaching experience, either as an instructor of record or as a teaching assistant, is required. Candidates who are qualified to teach undergraduate courses in data science or machine learning are preferred.

Application Instructions
Applications must be submitted online through the University of Chicago’s Academic Jobs website: Review of applications will begin on January 4, 2021 and will continue until all positions are filled.

The following materials are required:

cover letter;
curriculum vitae including teaching experience and publications;
description of teaching philosophy and experience; ability to interact with a diverse group of students is valued. Must include a list of courses that the candidate is qualified to teach;
applicants are required to request at least three confidential letters of recommendation via Interfolio.

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages diverse perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange. The University’s Statements on Diversity are at

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University’s Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-1032 or email with their request.