Assistant Professor, Computer Information Science (AA28030) at Minnesota State in Mankato

Job description

All Job Postings will close at 12:01 a.m. CT on the specified Closing Date (if designated). Working Title: Assistant Professor, Computer Information Science (AA28030) Institution: Minnesota State University, Mankato Classification Title: State University Faculty Bargaining Unit / Union: 209: Inter Faculty Organization City: Mankato FLSA: Job Exempt Full Time / Part Time: Full time Employment Condition: Unclassified - Unlimited Academic Salary Range: $64,963.00 - $193,146.00 Salary Type: Depends on qualifications Application Deadline: Review of applications will begin on November 12, 2026 and continue until the position is filled. Position: Tenure-Track (Probationary*) Job Duties The department of Computer Information Science at Minnesota State University, Mankato invites applications for a probationary, Assistant Professor beginning August 17, 2026. This position supports the undergraduate and graduate programs in the Department of Computer Information Science at Minnesota State University, Mankato. Responsibilities include, but are not limited to, teaching undergraduate and graduate courses for the Computer Information Technology, Computer Science, Management Information Systems, Data Science, and Artificial Intelligence programs. Candidates must demonstrate motivation and expertise to support quality teaching, advising, professional development, and funded scholarly activity. The successful candidate will also actively participate in departmental committee work, curriculum design, assessment, and help create innovative strategies for student recruitment, retention, and program completion.. A typical faculty workload responsibility may include up to twenty four (24) credits of instruction per academic year. The successful candidate may need to teach in other areas as assigned and qualified. May be expected to develop and deliver face-to-face, hybrid, and on-line instruction at the Mankato campus, online, and/or at the university’s additional locations, as assigned. The successful candidate will collaborate with colleagues in curriculum design, instruction and evaluation, conduct research productively and mentor students in research, help create innovative strategies for student recruitment, retention, and completion, and may be expected to develop external grant funding opportunities. The successful candidate will be responsible for teaching undergraduate and/or graduate courses in advanced database, advanced data analytics, computer architecture, cloud computing, information security, network architecture, data engineering, computer vision, deep learning, or natural language processing, or other areas as assigned and qualified. All faculty members are expected to engage in scholarly or creative activity or research, continuing preparation and study, contribute to student growth and development, and in providing service to the university and community (See Article 22 and Appendix G of the IFO Master Agreement ) This position will advise undergraduate and graduate students in majors offered by the Computer Information Science Department. The successful candidate will demonstrate a commitment to active, applied learning and developing innovative ways to support learning, including project-based teaching pedagogies. The successful candidate will be knowledgeable about current industry trends and emerging research. This position will advise and mentor students, including graduate-level theses and other capstone papers. Minimum Qualifications Demonstrated ability to work effectively with individuals from a wide range of diverse backgrounds and to foster a professional environment that is inclusive, respectful, and equitable for all. Doctoral degree in Computer Science, Computer Information Science, Data Science, Information Technology, Management Information Systems, or a closely related field conferred on an official transcript by the date of appointment. Preferred Qualification Demonstrated experience fostering an inclusive, equ