[AISWorld] Use-inspired AI position at the McCombs School of Business

[Saar-Tsechansky, Maytal]

The University of Texas at Austin: McCombs School of Business: Department of Information, Risk, & Operations Management (IROM)



Position in Use-Inspired Artificial Intelligence



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 one tenure-track assistant professor position (starting Fall 2023) in the area of Use-Inspired Artificial Intelligence. We invite applications from diverse areas, including Computer Science, Information Systems/Management, Engineering, Decision Science, and Statistics.

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.

A successful candidate will be expected to contribute creatively and in depth to AI through research, teaching, and student mentorship. Ideal candidates will have a strong and active use-inspired research agenda, demonstrate strong communication skills, and will actively contribute to McCombs and to the AI community at UT Austin.

IROM is a vibrant, interdisciplinary, department that serves a large, growing, and diverse student body. We expect that the successful candidate will contribute to the department’s strengths, be a team player, and be comfortable in an interdisciplinary setting. More information about IROM and the McCombs School can be found at https://www.mccombs.utexas.edu/departments/irom

We are committed to recruiting, employing, and supporting highly-qualified faculty members with a wide range of backgrounds, ideas, and viewpoints, and we are dedicated to the principle that individuals be respected, their voices be heard, their contributions be valued, and that they enjoy equitable access to opportunities. We strongly encourage qualified candidates from underrepresented backgrounds to apply. Moreover, we encourage qualified candidates with demonstrable skills, expertise and accomplishments in diversity, equity, inclusion and accessibility to apply. Candidates are encouraged to include a brief discussion of how their demonstrable skills in diversity, equity, inclusion and accessibility will be reflected in their research, teaching and/or mentorship. We also value transparency and openness in science and encourage candidates to provide in their research statement a description of how these values are reflected in their work to date and their future research plans.

Further questions should be directed to Professor Maytal Saar-Tsechansky (maytal at mail.utexas.edu), Translational AI Faculty Search Committee Chair.

A background check will be conducted on applicants selected for the positions prior to appointment.

Application Instructions:



All application materials should be submitted via Interfolio at http://apply.interfolio.com/112339



Applications should include a cover letter (1 page), CV, a statement of research and teaching including accomplishments and plans (3 pages in total), 2 representative publications, and arrange for three recommendation letters to be sent separately. We will continue accepting applications until the position is filled but the search committee will begin reviewing applications on October 1st 2022. We expect to start conducting interviews shortly afterwards, including at the 2022 annual INFORMS conference at Indianapolis. Candidates interested in talking to us at major conferences this fall should ensure that their applications are complete before they attend.





Equal Employment Opportunity Statement

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.


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Maytal Saar-Tsechansky (she/her/hers) | Mary John and Ralph Spence Centennial Professor
Information, Risk, and Operations Management | The McCombs School of Business | The University of Texas at Austin
Machine Learning Lab<https://www.ml.utexas.edu/>, Scientific Advisory Board Member