> Markdown version of [/jobs/ext/4606766-mpcs-part-time-lecturer-artificial-intelligence-machine-learning](https://www.wearedevelopers.com/jobs/ext/4606766-mpcs-part-time-lecturer-artificial-intelligence-machine-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # MPCS Part-Time Lecturer - Artificial Intelligence / Machine Learning - **Company:** The University of Chicago - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $12,000.0 - $16,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Machine Learning, Information Technology - **Published:** November 6, 2026 - **Apply:** https://www.disabledperson.com/jobs/76388762-mpcs-part-time-lecturer-artificial-intelligence-machine-learning ## About the Role While university-level teaching experience is preferred, it is not strictly required. Successful applicants without university-level teaching experience will receive coaching and mentoring from more senior instructors before and during a new hire's first course., * A graduate degree in Computer Science or a related field at the time of appointment, or 5 years of relevant industry experience., * MS and/or PhD in Computer Science or a related field at the time of appointment, or 10 years of relevant industry experience; * Teaching experience in Computer Science or a related field at the undergraduate or graduate level, as either an instructor of record or a teaching assistant; * Work experience in a computing-related industry. ## Description This position is part-time and is not benefits-eligible. Courses will be assigned on a quarterly basis based on program need. Compensation is paid on a per-course basis in the teaching quarter(s). Applicants must currently be authorized to work in the U.S. Courses run for nine weeks each academic quarter, with the tenth week reserved for a final project or examination. Instruction may be delivered in person, remotely, or in a hybrid format, subject to program needs and the required university approvals. Courses may be scheduled during the daytime (meeting one to three times per week for up to three hours total) or in the evening (meeting once per week for up to three hours). Specific meeting days and times are set in consultation with the instructor.