The Department of Information Science at the University of North Texas (UNT) invites applications for a Full Professor position. Position start date will be either Spring 2022 or Fall 2022.
We are seeking exceptional candidates with interests in a wide range of topics within the theoretical, machine learning, and computational foundations of data science. The candidate will teach, conduct research, and provide service and leadership in an academic position with emphasis in Data Science. The candidate must demonstrate a record of outstanding research accomplishments and have the ability to design and deliver courses in a variety of formats, including online and hybrid modalities in Data Science. The candidate is expected to teach Data Science undergraduate, graduate, and doctoral level courses and advise students in Data Science research. They are expected to work closely with doctoral students and to serve on dissertation committees. Applicants will be expected to have outstanding research accomplishments in research publications and funded research, and academic credentials that demonstrate their ability to conduct independent world-class research and attract external funding. This is a nine month, full-time, tenure-track position. We seek candidates who will provide inspiration and leadership in research and teaching, who can leverage the strengths of the department’s dynamic faculty and programs, and who will build collaborative relationships in the University and profession.
The College of Information and Department of Information Science are committed to creating a learning community that reflects and enacts the values of diversity, equity and inclusion that inform academic excellence. We encourage applicants who may enhance our representational diversity but especially whose research, teaching, and community engagement will contribute to diverse, equitable, and inclusive learning and working environments for our students, staff, and faculty.
An offer of employment for this position will be made dependent upon available funding.
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