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About the position
As part of a sustained, multiyear, strategic growth initiative, the School of Computer Science (CS; https://www.ou.edu/coe/cs) in the Gallogly College of Engineering (GCoE; https://www.ou.edu/coe/cs) at the University of Oklahoma (OU; https://www.ou.edu) seeks applications for a tenure-track assistant professor position in the area of hybrid machine-learning/first-principles modeling with a targeted start date of Fall 2024. We particularly seek candidates whose core expertise will allow OU to synergistically leverage existing first-principles modeling strengths across GCoE as well as existing strengths in machine learning and data mining in CS. We further seek candidates whose research, teaching, and service have prepared them to be integral contributors to the advancement of our welcoming community. Candidates who fill this position should look to support OU's strategic research verticals (https://www.ou.edu/research-norman/centers-institutes/strategic-vertical-institutes) and GCoE's strategic plan (https://ou.edu/content/dam/CoE/Pictures/GCoE%20Strategic%20Plan%202020-25%20Update%2007-27-21.pdf), and be prepared to engage in collaborative research. We also welcome applicants whose research interests support artificial intelligence (AI) X and computational-X.
The University of Oklahoma (OU) is a Carnegie-R1 comprehensive public research university known for excellence in teaching, research, and community engagement, serving the educational, cultural, economic, and healthcare needs of the state, region, and nation from three campuses: Norman, the Health Sciences Center in Oklahoma City, and the Schusterman Center in Tulsa. OU enrolls over 32,000 students and has more than 2,600 full-time faculty members in 21 colleges. The School of Computer Science is growing rapidly in size and impact. As of Spring 2024, it has 26 faculty (https://www.ou.edu/coe/cs/people) from a wide variety of backgrounds and more than 950 students; features student-centric initiatives; has vibrant research and teaching programs aligned with OU's strategic plan (https://www.ou.edu/leadon); and is a key partner in OU's world-class Data Science and Analytics Institute (https://www.ou.edu/coe/dsai).
The University of Oklahoma invests in its faculty by providing support and resources through our Center for Faculty Excellence and Vice President for Research and Partnerships Office. The Gallogly College of Engineering supports faculty development through mentoring, new faculty orientation series, and access to research and educational supports. We encourage candidates to apply who are seeking to work in a rapidly growing college with collegial interdisciplinary groups and strong academic units.
Qualifications
REQUIRED:
- Ph.D. in Computer Science or a related field.
- Able to effectively conduct and lead research.
- Able to effectively form research collaborations.
- Able to effectively teach computer science courses at all levels.
- Able to effectively advise M.S. and Ph.D. students.
PREFERENCES (NOT REQUIRED):
- Demonstrated passion for teaching as well as research.
- Evidence of excellent and innovative instruction.
- History of innovative research projects.
- Demonstrated ethos of care and support of students.
- Evidence of effective mentorship and guidance of research-active students.
- History of commitment to supportive environments in the classroom, office, and lab.
How to apply
Applicants should submit a cover letter explaining the applicant's interest in all aspects of the position, current C.V., 2-3 scholarly articles that best represent the applicant's research contributions, and complete contact information (including full mailing and e-mail addresses and telephone numbers) of three people willing to write letters of recommendation to http://apply.interfolio.com/139322. The cover letter may address examples of the candidate's approach to scholarship, research, and teaching. Additional materials may be requested at a later date. The search will remain open until filled.
Inquiries should be directed to the search committee chair: Dr. Dimitrios Diochnos, School of Computer Science, University of Oklahoma, diochnos@ou.edu, 405-325-2978.
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