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Tenured Associate / Full Professor in Computer Science more...
Location:Austin, TX
Company:The University of Texas at Austin
First posted:May 25, 2017
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Description

The Department of Computer Science of the University of Texas at Austin invites applications for tenured Associate Professor or Full Professor positions. Outstanding candidates in all areas of Computer Science will be considered, particularly in: computer vision, machine learning, cybersecurity and formal methods.

The department is ranked among the top ten computer science departments in the country. It has 44 tenured and tenure-track faculty members across all areas of computer science. Many of these faculty participate in interdisciplinary programs and centers in the University, including the Texas Advanced Computing Center (TACC), and those in Computational and Applied Mathematics, Computational Biology, and Neuroscience.

Austin, the capital of Texas, is a center for high-technology industry, including companies such as Dell, IBM, Advanced Micro Devices, 3M Corporation, National Instruments, Apple Computer, Inc., AT&T and Samsung. For more information about the department, please visit  (please use the apply button below).edu.

 

Qualifications

All tenured positions require a Ph.D. or equivalent degree in computer science or a related area at the time of employment. Successful candidates are expected to pursue an active research program, to teach both graduate and undergraduate courses, and to supervise graduate students in research. The department is committed to building a diverse faculty and we are interested in candidates who will contribute to diversity and equal opportunity in higher education through their teaching, research, and service.

EEO 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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