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Job ID: 133373

Research Assistant Professor
University of North Texas


Date Posted Nov. 12, 2019
Title Research Assistant Professor
University University of North Texas
Denton, TX, United States
Department
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Research Professor
    Assistant Professor
  • Computer Engineering
    Computer Science
 
 

The University of North Texas (UNT), a Tier 1 Research Institution (Carnegie Classification as a Doctoral University: Highest Research Activity), invites applications for a Research Assistant Professor in Computer Science and Engineering.

Artificial Intelligence and Smart Sensors are two of the established college-wide priorities for the College of Engineering.

The department plans to contribute to these priorities by hiring faculty in our existing strength areas of Algorithms and Computational Science as well as Artificial Intelligence and Data Science with the intention to apply these skills to acquired sensor signals. Ideal candidates have experience in applied signal processing on Terabyte-scale data sets.

Candidates are expected to be highly collaborative, and experience with large collaborations involving multiple university partners is preferred. Additionally, candidates will have applied statistical and machine learning methods to a variety of signal processing problems including analysis of video, audio, inertial sensor signals.

Candidates are expected to develop a strong research program funded by external sources, support and mentor graduate students, and provide service to the University and the profession. Candidates are not required, but my have opportunities to teach CSE undergraduate and graduate courses, and candidates with previous teaching experience are encouraged to apply.
This position will begin December 1, 2019.

The Computer Science and Engineering department is home to 35 faculty, over 100 Ph.D. students, over 100 M.S. students, and almost 1300 bachelor students. We offer a Ph.D. degree in Computer Science and Engineering, M.S. degrees in Computer Science and Computer Engineering, ABET-accredited B.S. degrees in Computer Science and Computer Engineering, and an ABET-accredited B. A. degree in Information Technology.

Application Procedure:
Submit nominations and questions regarding this position to Dr. Barrett Bryant (Barrett.Bryant@unt.edu).

Application Deadline:
The committee will begin its review Nov 11, 2019, and continue to accept applications until the position is closed.

The University:
UNT is the nation’s 33rd largest public university and the largest, most comprehensive in the Dallas-Fort Worth area, one of the fastest growing metropolitan areas with a population of about 7 million people, ever-increasing industrial and business activities, and a reasonable cost of living. The vibrant UNT College of Engineering has more than 100 faculty members. The college’s faculty also boast two National Academy memberships, more than 20 faculty fellowships across more than 15 societies, and five NSF CAREER Awards. The college is equipped with numerous state-of-the-art facilities including a recent $10 million boost to the Center for Agile and Adaptive Additive Manufacturing. The college plans to hire 17 tenure and tenure track faculty this year and to expand the college faculty by 50% in the next 5 years.

Minimum Qualifications:

Ph.D. in Computer Science, Statistics, Applied Math, Physics, or a closely related field.

A strong publication record and the potential to succeed in securing research funding and mentoring graduate students are required.

The University of North Texas System and its component institutions are committed to equal opportunity and comply with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University of North Texas System and its component institutions do not discriminate on the basis of race, color, sex, sexual orientation, gender identity, gender expression, religion, national origin, age, disability, genetic information, or veteran status in its application and admission processes, educational programs and activities, and employment practices.


 
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