Postdoctoral Research Fellow, Department of Information, Risk, and Operations Management

Job Details

Job Posting

Title:

Postdoctoral Research Fellow, Department of Information, Risk, and Operations Management

Hiring Department: Department of Information, Risk, and Operations Management

Position Open To: All Applicants

Weekly Scheduled

Hours:

40

FLSA Status: Exempt

Earliest

Start Date:

Immediately

Position Duration: Expected to Continue Until Aug 31, 2027

Location: UT MAIN CAMPUS

Professor Maytal Saar-Tsechansky and the Department of Information, Risk, and Operations Management (IROM) in the McCombs School of Business at the University of Texas at Austin invites applications for a postdoctoral researcher position. The research is focused on a use-inspired Artificial Intelligence (AI) research agenda that addresses challenges in developing AI systems and human-AI collaboration methods to reliably improve outcomes in health care and other high-impact contexts, benefiting people, organizations, and society at large.

We invite applications from varied relevant academic backgrounds, including Computer Science, Engineering, Statistics, and Data Science. Successful candidates will have a Ph.D. in a relevant field of research, with a relevant record and interest in use-inspired AI, who are independent, and have an ability and interest to initiate and drive research projects and engage productively with an interdisciplinary team.

Successful candidates will join a team of faculty and Ph.D. students, enjoy mentorship opportunities, gain unique access to and collaboration with professionals performing life-saving, high-stake decision-making, and join a vibrant AI research community at the University of Texas at Austin, become members of The University of Texas at Austin's Machine Learning Laboratory (), and contribute to The University of Texas at Austin's Use-Inspired AI cluster, which serves as an interdisciplinary research platform for use-inspired AI research on the UT Austin campus.

We seek candidates with a Ph.D. in a relevant field of research, with a strong research record and interest in use-inspired AI research, demonstrated research independence, and the ability to serve in a central role within an interdisciplinary team.

Texas McCombs is a top business school at the center of one of the most innovative cities in the U.S. The McCombs community champions hands-on experiences alongside the ground-breaking research and thought-leadership of a world-class faculty. The collaborative spirit and enterprising drive of the Longhorn alumni network is embedded in our culture, making us human-centered and future-focused in all our endeavors.

What starts here really does change the world.

For more information about the McCombs School of Business please visit https://(Use the "Apply for this Job" box below)./

The position centers on use-inspired AI research at the frontier of productive, reliable, and clinically grounded decision support, developing AI systems and human-AI teaming methods that leverages opportunities and tackles constraints in real world contexts. In collaboration with a leading university-based medical center, the position offers access to high-stakes workflows, rich real-world data, and deployment pathways, enabling research that couples real deployment targets with core methodological innovation.

The goal is to produce broadly applicable advances that improve outcomes in healthcare and translate to broad organizational and societal settings beyond medicine.

This postdoctoral research fellow position is grant-funded with an initial employment period of one year. Reassignment will be based on performance, progress toward research goals and continuation of funding. The position can start as early as Spring, Summer, or Fall 2026.

• The position is in-person in Austin Texas. The postdoctoral researcher will be a key member of the research team, responsible for driving, coordinating, and conducting research, and will have opportunities to initiate research and mentor Ph.D. students.

• Ph.D in research that is relevant to use-inspired AI, interest in human-AI collaboration including in the context of LLMs, and knowledge in…