Assistant Professor, Computer Information Science - IFO; AA

Position: Assistant Professor, Computer Information Science - IFO (AA27054)

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 - IFO (AA27054)

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 - $

Salary Type: Depends on qualifications

Final date to receive applications: Review of applications will begin on May 6, 2026 and continue until the position is filled.

Position: Tenure-Track (Probationary*)

Job Description

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.
• All faculty members are expected to engage in scholarly or creative activity or research, in continuing preparation and study, in contributing 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)
• The successful candidate may need to teach undergraduate and 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.
• The successful candidate will demonstrate a commitment to active, applied learning and developing innovative ways to support learning, including project-based teaching pedagogies.
• Faculty will be knowledgeable about current industry trends and emerging research.
• This position will advise and mentor students, including graduate-level theses and other capstones papers.

Minimum Qualifications

• 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.
• 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.

Preferred Qualification

• Ability to teach a variety of topics at the undergraduate and graduate level in advanced database, advanced data analytics, computer architecture, cloud computing, information security, network architecture, data engineering, computer vision, deep learning, or natural language processing.
• Demonstrated commitment to active, applied learning and developing innovative ways to support learning, including…