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Non-Tenure Track Statistics Professor
McCombs School of Business in the Austin, Texas
 
 
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Date Posted October 04, 2019
Category
Graduate Business School -Faculty
Employment Type Full-time
Application Deadline Open until filled
 
 
 

Description

The McCombs School of Business at the University of Texas at Austin invites applications for an open-rank, full-time non-tenure track teaching position in Statistics to begin on or before August 1, 2020. Applications will be considered at any level and the salary will be commensurate with the candidate's experience and qualifications, and with our position as one of the top business schools in the nation.

The McCombs School of Business sits right in the middle of one of the most intellectually vibrant universities, and one of the most desirable cities, in the world. As an Equal Opportunity Employer, the McCombs School is committed to hiring a diverse faculty as we work to foster excellence and innovation in our curriculum and to give our population of 4700+ undergraduates and 1700+ postgraduates as rich and varied an educational experience as possible. As a campus with a continually growing diverse student body, we strongly encourage women, minorities, and individuals with a demonstrated commitment to diversity and inclusion to apply.

Qualifications

Successful candidates will teach undergraduate and master's courses, contribute to crafting the expansion of the college's data-science offerings, and be involved in service to the university and profession. The minimum qualifications are: 1) a PhD in statistics or a related field, and 2) demonstrated excellence in teaching. The statistics group at McCombs is committed to data-driven pedagogy in its undergraduate program, and candidates with an interest in and/or experience with conducting hands-on research in statistics and data science education will be at an advantage.

Application Instructions

Applications should be submitted via Interfolio. Please submit: a cover letter; your CV; a teaching statement that includes your vision for data science education in a business school; a brief summary of your research experience; and up to three letters of recommendation, which should speak directly to teaching.

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