The Heinz College of Information Systems and Public Policy at Carnegie Mellon University invites candidates to apply for a teaching postdoctoral fellowship position. The teaching post-doctoral fellowship is designed for those who are interested in exploring teaching careers or research plus teaching careers. They will be mentored by outstanding teaching, research, and practice faculty at Heinz College and will benefit from the rich inter-disciplinary environment.
We seek candidates that have expertise and could offer courses to graduate students in AI, AI Management, and Applied AI including topics such as responsible AI, introduction to AI, operationalizing AI, agentic AI, python, machine learning, introduction to deep learning, or large language model systems. We are seeking an individual committed to engaging and effectively training graduate students with a wide range of prior training. We also welcome applicants who are intrigued by the rapidly evolving governance, management, and use of AI in government, non-profit organizations, and business.
Postdoctoral fellows are expected to teach two semester equivalent courses per semester. Fellows are expected to pursue research related to their interests under the supervision of a tenure track faculty member. Postdoctoral fellows are also expected to participate actively in the intellectual life of the College and become involved in Carnegie Mellon’s rich interdisciplinary community.
The postdoctoral fellowship position will run from August 1, 2026, to July 31, 2028. This is a full-time, benefits-eligible position.
The application deadline is May 15, 2026 Applications will be considered on a rolling basis.Applications should be submitted through Interfolio.
About Heinz College
The Heinz College of Information Systems and Public Policy is home to two internationally recognized schools: the School of Information Systems and Management and the School of Public Policy and Management. The unique colocation of these two schools sets Heinz College apart to tackle society’s most complex problems by teaching our students a firm understanding of policy, technology and analytical foundations, and the management skills to deploy solutions for maximum impact – the intersection of people, policy, and technology to approach complex societal problems. For more information, please visit www.heinz.cmu.edu
Heinz College adheres to four basic principles of being grounded in real-world problem solving; staying ahead of the curve in innovation; nurturing opportunity; and developing compassionate leaders.
● Ability to develop and deliver graduate-level courses in Applied AI and topics such as responsible AI, operationalizing AI, agentic AI, python, machine learning, introduction to deep learning, or large language model systems
● Excellent interpersonal and communication skills
● Background in teaching or being a teaching assistant highly preferred
Materials to be submitted:
●Cover letter of one to two pages briefly stating the applicant’s academic background, research agenda, interest in the program.
●CV.
●Teaching Statement (titles and short descriptions of at least two courses that the candidate is eligible to teach) and a discussion of any relevant experience in teaching a group of intellectually curious students with a wide range of prior training.
●Research Statement (Brief statement of research interests and a discussion of how it supports excellence in the classroom)
●Two writing samples of scholarly work.
●Unofficial transcripts from all graduate-level degrees; and
●Two reference letters.
Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.
At the SEI, we research complex software engineering, cybersecurity, and AI engineering problems; create and test innovative technologies; and transition maturing solutions into practice. We have been working with the Department of Defense, government agencies, and private industry since 1984 to help meet mission goals and gain strategic advantage.
