The AI-Human Research Center at Carnegie Mellon University (CMU) invites applications for two-year Postdoctoral Fellows positions to conduct cutting-edge research on improving workplace wellbeing with Generative AI and Large Language Models (LLMs). Robert Kraut, Haiyi Zhu, Sherry Wu, and Yi-Chia Wang in the Human-Computer Interaction Institute at CMU and Diyi Yang at Stanford University are available as mentors. Initial positions will be full-time in Pittsburgh, PA. CMU offers a vibrant interdisciplinary research environment across the Human-Computer Interaction Institute, Language Technologies Institute, and School of Computer Science, with extensive opportunities for collaboration, mentorship, and professional development.  

Project Overview:

This project investigates how LLMs can be used to train workers for social skills in different environments—for example, training supervisors to better support the customer service representatives (CSRs) they oversee to promote their wellbeing; training CSRs to improve their ability to interact with a wide variety of customers; and training novice mental health providers in helping skills. By building and deploying a training environment in which trainees interact with realistic virtual employees, customers or patients and receive appropriate feedback, the research aims to reduce worker stress, improve interaction quality, and advance understanding of human–AI collaboration in organizational settings.

The postdoctoral researcher will design and implement LLM-powered conversational agents and training systems, develop feedback and assessment mechanisms, conduct human-subject studies and mixed-method analyses, build end-to-end prototypes, collaborate closely with faculty, students, and industry partners, and publish results in top-tier venues in NLP, HCI, and AI.

Required Qualifications:

Applicants must have:

* A PhD in a relevant research field, including Computer Science, Information Science, HCI, AI/ML, Communication, Organizational Behavior, or Psychology

* Strong background in NLP or generative AI

* Experience working with or fine-tuning large language models

* Demonstrated technical ability and rapid prototyping

* An active publication record in leading conferences or journals

Preferred Qualifications:

We are especially excited about candidates who have:

* Interest in wellbeing, mental health, organizational behavior, and interpersonal communication

* Background in evaluation of interactive AI systems

* Systems implementation experience (front-end + backend development)

* Experience collaborating with industry partners

Applicants should submit:

* A CV

* At least two letters of reference

* A brief research statement describing interests and fit with the project

Applications will be reviewed on a rolling basis until the position is filled.

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.

About Carnegie Mellon University

Carnegie Mellon (www.cmu.edu) is a private, internationally ranked research university with programs in areas ranging from science, technology and business, to public policy, the humanities and the arts. More than 12,000 students in the university’s seven schools and colleges benefit from a small student-to-faculty ratio and an education characterized by its focus on creating and implementing solutions for real problems, interdisciplinary collaboration and innovation. A global university, Carnegie Mellon’s main campus in the United States is in Pittsburgh, Pa. It has campuses in California’s Silicon Valley and Qatar, and programs in Africa, Asia, Australia, Europe and Mexico.

Connections working at Carnegie Mellon University