University of Texas at Austin
Information, Risk, and Operations Management Department
The University of Texas at Austin: McCombs School of Business: Department of Information, Risk, & Operations Management (IROM)
The Department of Information, Risk, and Operations Management (IROM) at the McCombs School of Business at the University of Texas at Austin invites applications for two tenure-track assistant professor positions (starting Fall 2023) in the areas of Use-Inspired Artificial Intelligence and Business Analytics. We invite applications from diverse areas, including Computer Science, Information Systems/Management, Engineering, Decision Science, and Statistics. Applicants who believe they are a good fit for both positions are encouraged to apply to both.
The search committees will begin reviewing applications on October 1, 2022, and the searches will remain open until the positions are filled.
Assistant Professor Position in Use-Inspired AI
We are particularly interested in scholars pursuing a use-inspired AI research agenda in the context of important business, organizational, and societal challenges. We seek scholars whose research agenda aims to advance AI methodology inspired by considering AI in business-relevant contexts, and where the research simultaneously informs progress in AI and advances business/organizational/societal goals.
Successful candidates will join a vibrant AI research community within McCombs and across the University, become core members of The University of Texas at Austin’s Machine Learning Laboratory (https://ml.utexas.edu/) and contribute to The University of Texas’ at Austin’s Translational AI Cluster that serves as an interdisciplinary research platform for use-inspired AI research on campus.
Questions should be directed to Professor Maytal Saar-Tsechansky (firstname.lastname@example.org), Translational AI Faculty Search Committee Chair.
Application instructions and submission https://apply.interfolio.com/112339
Assistant Professor Position in Business Analytics
We are particularly interested in scholars who are applying quantitative and/or data-driven methods to business problems. A successful candidate will be expected to have an active research program, teach business analytics courses at the undergraduate and graduate levels, supervise graduate students, contribute to the department’s strengths, be a team player, and be comfortable in an interdisciplinary setting.
Questions should be directed to Professor Guoming Lai (email@example.com), Business Analytics Faculty Search Committee Chair.
Application instructions and submission http://apply.interfolio.com/112357