Assistant Professor of Computer Science; Artificial Intelligence and Data Science

The Department of Computer Science at Tennessee Tech University invites applicants for an Assistant Professor position with the primary responsibility of teaching artificial intelligence and data science as part of our new B.S. in Artificial Intelligence. This full-time, nine-month, tenure-track position begins August 2026.

Selected candidates will be student-centered and expected to teach undergraduate and graduate courses primarily in AI, machine learning, and data science, with an initial focus on undergraduate courses. They will contribute to curriculum development and participate in scholarly activities centered on teaching, learning, and/or computer science related pedagogy. This includes publishing research papers and pursuing external funding. They will also direct projects and research of students at the undergraduate and graduate levels;

serve on committees at the department, college, and university levels; engage in professional and public service; and advise students on professionalism and career opportunities.

(Use the "Apply for this Job" box below). Applicants will be required to electronically upload a cover letter, curriculum vitae, teaching philosophy (including philosophy and experience teaching students from ethnically and socio-economically diverse backgrounds), research statement, copies of transcripts (official transcripts for all degrees conferred required upon hire), and email contact information for three references who will be contacted via email to provide a reference letter if selected for interview.

Applications without all required materials are incomplete and will not be considered. Screening of applications begins January 15, 2026; open until filled. Tennessee Tech University is an AA/EEO employer.

Minimum qualifications:

Earned doctorate in computer science, AI, data science, or a closely related field by start date of employment; an ability and desire to strive for teaching excellence in AI and data science at the undergraduate and graduate levels; potential to engage in externally funded research; engagement in scholarly activities as demonstrated by peer-reviewed journal and conference publications; and effective communication and interpersonal skills.

Preferred qualifications:

Expertise in the areas of AI and data science; relevant teaching experience; experience with best practices in the development, deployment, and management of AI and data science tools; and industry experience.