Job Description

Department Summary
The Department of Information Science is part of the College of Information and is a member of the iSchools and a member of the iCaucus. The Department of Information Science promotes the understanding of access to and use of data and information through teaching, research and service activities. The department prepares data and information professionals of the highest quality to serve in dynamic roles locally, nationally and globally. Faculty members of the department measure their success by the success of their students and the quality of intellectual contributions to the profession and society. The department offers programs in Data Science, Library Science and Information Science at the undergraduate, graduate and doctoral levels. The department has an established Master of Science in Data Science (MS-DS) program, the Bachelor of Science in Data Science program (BS-DS), Grad-Track in Data Science (BS-DS and MS-DS) program, and a PhD in Information Science with concentration in Data Science. Detailed information about the department can be found at https://informationscience.unt.edu/.

UNT has a highly diverse campus with a wide range of languages spoken in addition to English. We welcome candidates who have experience with HSI/MSIs and/or who speak Spanish, Vietnamese, American Sign Language, Chinese (Cantonese, Mandarin and other variations), Arabic, Tagalog, Farsi, French, or/and Yoruba.
Position Summary
The Department of Information Science at the University of North Texas (UNT) invites applications for a tenure-track Assistant/Associate Professor position. Position will begin Fall 2024. We are seeking exceptional candidates with interests in a wide range of topics within the theoretical, machine learning, data visualization, and computational foundations of data science. The candidate will teach, conduct research, and provide service in an academic position with emphasis in Data Science. The candidate must demonstrate a record of 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. Exceptional candidates at the rank of Associate Professor will be considered.
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.
Minimum Qualifications
The minimum requirement for appointment is an earned doctorate in Data Science, Computer Science, Computer Engineering or other related fields at the time of appointment.
Preferred Qualifications
Candidates will demonstrate evidence of effective teaching, research, and scholarship with experience/expertise in the broad areas of Data Science, Information Science, and Computer Science. Preference will be given to candidates who have been active in publication and have a demonstrated record of funded scholarly research and publication.
Required License / Registration / Certification
Physical Requirements Ability to communicate
Area of Specialty Data Analytics, Machine Learning, Data Visualization, Big Data, Data Mining, Data Engineering, Information Retrieval, Artificial Intelligence, Data and Information Quality, Data and Information Security and Privacy, Biomedical Informatics.
Security Sensitive This is a security sensitive position.
EEO Statement
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.