Important dates for faculty positions that begin Fall 2025:
- Application Opens: August 5, 2024
- Teaching Track early review deadline: October 2, 2024
- Application Closes: December 11, 2024 for Tenure and Research Tracks
New: Teaching Post-Doc position [Open year round]
The Machine Learning Department (MLD) in the School of Computer Science (SCS) at Carnegie Mellon University (CMU) invites applications for our Postdoctoral Teaching Fellowship. This is a one-year position, beginning Fall 2025, with the possibility of renewal for a second year.
We seek PhD graduates with 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 at all levels including undergraduates, Master’s, and PhD 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 1st, but applications will be considered year round.
Multiple Teaching Track Positions [We are now accepting applications for positions starting in Fall 2025!]
The Machine Learning Department at Carnegie Mellon University has openings for Teaching Faculty to deliver our world class educational material to diverse student audiances, and to help evolve the teaching of machine learning within and outside our campus. As the world's first and possibly only 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 Masters 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, please read the School of Computer Science - Policy on Teaching Track Appointments.
Multiple Tenure Track Positions [We are now accepting applications for positions starting in Fall 2025.]
The Machine Learning Department of the School of Computer Science at Carnegie Mellon University invites applications for tenure-track positions at the rank of Assistant Professor, as well as positions at the level of Associate and Full Professor. All areas of machine learning and artificial intelligence will be considered. Applicants are expected to have an active research program and a commitment to teaching excellence.
The Department occupies a privileged position in the world of machine learning, in part as the world's first and possibly only academic Machine Learning Department. The Department has close relationships through shared faculty and active collaboration across the university, especially with the Statistics Department, the School of Public Policy, and other academic units in the School of Computer Science, including the Computer Science Department, Language Technologies Institute, Computational Biology Department, Robotics Institute, Human-Computer Interaction Institute, and Software Engineering, and Societal Computing. We seek applicants who will thrive in this interdisciplinary setting.
Carnegie Mellon is highly supportive of dual career candidates and strongly encourages them to apply.
We also particularly encourage applications from candidates who have a demonstrated track record in mentoring and nurturing female and underrepresented minority students.
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.
Carnegie Mellon University abides by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability. |