School of Computing Professional Practice Assistant Professor

Overview

The School of Computing (SoC) in the College of Engineering at Utah State University (USU) invites applications for multiple Professional Practice Faculty positions at the Logan campus. These are full-time, benefited, non-tenure-track appointments beginning between January and August 2026. USU’s School of Computing is expanding to meet strong student demand and new opportunities in Artificial Intelligence/Machine Learning and Software Engineering, while continuing to strengthen its long-standing Computer Science program.

Professional Practice Faculty are dedicated teaching faculty who focus on high-quality instruction, mentorship, and curricular innovation that connect academic learning with real-world application.

We seek candidates who combine technical expertise with a passion for teaching and mentoring. Applicants with significant industry experience who can bridge theory and practice and prepare students for success in modern computing careers are especially encouraged to apply.

We welcome applicants with strong academic or professional backgrounds in Computer Science, Software Engineering, or related computing disciplines. The School has particular needs in:

• Software Engineering
• Artificial Intelligence and Machine Learning

We also welcome applicants who can make meaningful contributions across the broader Computer Science curriculum, including areas such as programming, software design, operating systems, web and mobile development, UI/UX design, cybersecurity, and programming languages.

Candidates with industry experience—especially those who have led software development or AI-driven projects—are highly encouraged to apply. The School seeks faculty who are enthusiastic about teaching, mentoring, and helping students apply computing skills to real-world challenges.

Successful candidates will demonstrate a commitment to teaching excellence, student engagement, and curriculum innovation that supports the growth and future direction of the School of Computing.

Responsibilities include:

• Teaching undergraduate courses in face-to-face, broadcast, online, or blended formats.
• Developing and updating course materials that reflect current technologies and practices in computing.
• Mentoring and advising students, supporting their academic and professional development.
• Contributing to program and course development, particularly in AI, software engineering, and core computer science.
• Participating in departmental service and outreach to strengthen the School’s connection with industry and community partners.

The School values faculty who are collaborative, reliable, and positive contributors to our shared mission. Ideal candidates will be collegial team members who work effectively with colleagues to enhance teaching quality, improve programs, and create an inclusive, supportive learning environment for students and peers alike.

Minimum Qualifications:

• M.S. in Computer Science or a closely related discipline
• Ability to serve as a mentor, advisor, and role model to students
• Ability to work productively and cooperatively with colleagues
• Excellent oral, written, and problem‑solving skills

Preferred Qualifications:

• Ph.D. in Computer Science or a closely related discipline
• Extensive industry experience in software development
• Successful prior teaching experience
• Successful prior online or distance education experience
• Experience with different learning technologies

Along with the online application, please include:

• Resume/CV to be uploaded at the beginning of your application in the Candidate Profile under “Resume/CV”.
• Names and contact information of three professional references as part of your Candidate Profile (reference letters will only be solicited from final candidates).

The documents listed below to be uploaded at the beginning of your application in the Candidate Profile under “Documents 1-10”:

• Cover letter summarizing your motivation, qualifications, experience, and career goals.
• A brief teaching statement that explains your approach to teaching and describes AI/ML courses you would like to develop and existing Computer Science/Computer…