Faculty Openings in the Machine Learning Department

Applications for faculty positions that begin in fall 2025 are closed. We will update this page when new deadlines are available.

New: Teaching Post-Doc Position (open year-round)

The Machine Learning Department invites applications for our Postdoctoral Teaching Fellowship. This is a one-year position, beginning in fall 2025, with the possibility of renewal for a second year.

We seek Ph.D. graduates with a deep understanding of machine learning, data science and computer science, with a demonstrated interest in teaching, and who aim to gain teaching experience. The Machine Learning Department is uniquely situated to offer both introductory and advanced courses in machine learning. The department’s course offerings draw students from all levels, including undergraduates, master’s and Ph.D. students, both from within the School of Computer Science and from other disciplines. The individual filling this position will have the opportunity to teach or co-teach lecture courses and to work with faculty to continue developing our curriculum in the rapidly advancing field of machine learning.

We also particularly encourage applications from candidates who have a demonstrated track record in tutoring, mentoring and nurturing female and underrepresented minority students.

Candidates may start in either the fall or the spring. Initial review will be performed on applications received by March 1, but applications will be considered year-round. 

Teaching Track Positions (currently not accepting applications)

The Machine Learning Department has openings for teaching faculty to deliver our world-class educational material to diverse student audiences, and to help evolve the teaching of machine learning within and outside our campus. As the world's first academic Machine Learning Department, we occupy a unique position in defining the standard curriculum for the field — one that is used as a template by many other universities. With the increasing societal prominence of machine learning in recent years, demand for our courses continues to grow steeply, and requests for us to serve students beyond our local campus have grown significantly.

The individual filling this position will teach introductory and/or advanced machine learning courses to our current students, and may also help evolve our machine learning curriculum, including developing new online and technology-assisted materials to improve educational outcomes and to extend our reach. They will work closely with the department head and other faculty to develop a strategic plan for taking advantage of new online and technology-assisted educational options over the coming decade. They may also oversee aspects of the educational program, e.g., admissions to our Ph.D. and master's programs, and advise undergraduate students majoring in artificial intelligence or minoring in machine learning. 

Candidates should have a Ph.D. with deep understanding of machine learning and a background of demonstrated excellence and dedication to teaching. Candidates must be prepared to teach extensive lecture courses at the advanced undergraduate and introductory/intermediate graduate-level and also be prepared to work with other faculty in the department to establish, improve, and standardize the curriculum.  Research is not required but is supported. 

For more information about teaching faculty appointments at Carnegie Mellon, read the SCS Teaching Track Appointment Policy.

Open Rank Faculty, Delphi Group

We welcome new faculty at any rank and any track (tenure, research, systems, teaching) to join us in leading the Delphi Group in the coming decade, to develop and deploy the technology and science that are urgently needed for epidemic tracking and forecasting. Learn more about Delphi.