Adjunct Assistant Professor-Data Visualization-CAPP
The University of Chicago

Chicago, Illinois

Posted in Education and Training

Job Info


The Department of Computer Science at the University of Chicago is seeking qualified applicants for the position of Adjunct Assistant Professor of Computer Science to teach sections of Data Visualization in the Master of Science in Computational Analysis and Public Policy Program (MSCAPP during the 2022 Autumn Quarter (September - December 2022). The goal of the course is for students to gain a practical knowledge of the theory of visualization (such as the grammar of graphics) as well as hands-on experience with contemporary visualization tools (such as d3).

This adjunct faculty position will be appointed to an initial one-quarter term, with possibility of renewal for future terms.

Courses are held for nine weeks during each academic quarter, with a tenth week for a final project or exam. Instruction is expected to be primarily in person, with some limited opportunities to offer remote or hybrid courses. Courses can meet in the daytime (meeting 2-3 times a week for a total of up to three hours) or in the evening (meeting once per week for up to three hours). The exact day(s)/time(s), are determined in consultation with the adjunct faculty member.

This position is part-time and is not benefits eligible. This is not a salaried position; adjunct faculty are paid on a per-course basis in the quarter(s) when they teach. Applicants must currently be authorized to work in the U.S.


One of the following:

  • A doctorate in Computer Science or a related field at the time of appointment
  • A masters degree and 4 years of relevant professional experience.
Preferred Qualifications:
  • Teaching experience in a professionally-oriented Masters program as an instructor of record.
  • Work experience in a computing-related industry.

Application Instructions

The following materials are required:
  • Cover letter detailing teaching experience and interests
  • Curriculum vitae
  • A list of three references must include name, title, employer/school and email address
The following optional materials may be submitted:
  • Teaching evaluations from past teaching at the university level

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