Special Information This position is an on-site position which requires the incumbent to complete their work primarily at an NAU site, campus, or facility with or without accommodation. Opportunities for remote work are rare.
About the Department/College Northern Arizona University (NAU) invites applications for multiple full-time, tenure-track assistant professor positions to infuse expertise in applications of Artificial Intelligence and Machine Learning (AI/ML) across its curriculum with a specific focus on building capacity within several key areas of recognized research excellence.
About the Position Individuals recruited as part of this initiative will join a university-wide faculty community that is committed to providing access to innovative academic programs, passionate about student success, and collaboratively leading world-class scholarly programs. A specific goal of this hiring initiative is to add robust expertise in applications of AI/ML to specific research areas at NAU that are already vibrant, productive, and well-recognized both nationally and internationally as leading research programs.
NAU is particularly interested in applicants with a research focus aligned with any of the following thematic areas:
- Engineering of AI/ML-autonomous systems with applications to remote applications to remote sensing/mapping; examples may include edge computing & real-time sensor fusion
for perception, intelligent path planning, human-machine interfaces, etc.
- AI/ML-enabled approaches to microbiome science related to precision medicine, human health or human performance.
- AI/ML applications in forestry and/or hydrological systems; examples may include ecosystem process modeling, predicting wildfire risk & recovery, climate forecasting, water resource management, etc.
- AI/ML-supported innovations to enhance teaching, learning, and assessment in STEM and data science education.
Candidates will be expected to develop a productive research program that synergizes with existing NAU research initiatives to address timely and significant topics in the fields listed above. Successful candidates will have an academic home in an appropriate department/school/college commensurate with their training and experience. Potential academic units associate with the research areas listed above include, but are not limited to:
- Department of Mathematics and Statistics
- Department of Mechanical Engineering
- Department of Teaching and Learning
- School of Informatics, Computing, and Cyber Systems
- School of Earth and Sustainability
- School of Forestry
Additionally, successful candidates will embrace NAU’s teacher-scholar faculty model by contributing to teaching and student mentorship at both the undergraduate and graduate level, including teaching of both new and existing course offerings. Ability to incorporate innovative uses of AI/ML in classroom and learning settings is desirable. NAU’s goal is to be the nation’s preeminent engine of opportunity, vehicle of economic mobility, and driver of social impact by delivering equitable postsecondary value in Arizona and beyond as described in NAU’s Elevating Excellence Strategic Roadmap.
Duties for faculty hired in this solicitation will include:
- Teaching at the undergraduate and graduate levels and mentoring students;
- Building and maintaining a vibrant and productive scholarly program, including securing extramural funding; and
- Contributing to service to the institutional, academic, and professional communities.
Minimum Qualifications
A Ph.D. in any discipline represented in our academic colleges, conferred by August 2026.
Preferred Qualifications
1. Demonstrated expertise in AI/ML methods, development, and applications in one or more of the following disciplinary areas:
- Engineering of AI/ML-autonomous systems with applications to remote sensing/mapping; examples may include edge computing & real-time sensor fusion
for perception, intelligent path planning, human-machine interfaces, etc.
- AI/ML-enabled approaches to microbiome science related to precision medicine, human health or human performance.
- AI/ML applications in forestry and/or hydrological systems; examples may include ecosystem process modeling, predicting wildfire risk & recovery, climate forecasting, water resource management, etc.
- AI/ML-supported innovations to enhance teaching, learning, and assessment in STEM and data science education.
2. Prior success in, or strong potential for, securing external funding at a level sufficient to maintain a vibrant research program;
3. Demonstrated record of research dissemination via peer-reviewed publications (journals, book chapters, etc.) and conference proceedings of recognized quality and impact;
4. Demonstrated record of teaching, student mentorship, and applications of AI/ML to enhance student learning;
5. Demonstrated interest in contributing to multi- and inter-disciplinary instructional and scholarly initiatives, including research and scholarly endeavors that develop and apply AI/ML-based methods to novel applications
6. Demonstrated record of resource dissemination advancing the adoption of AI/ML within any of the listed disciplinary areas, such as through public dissemination of important data sets, widely used software tools or models, or innovative educational resources.
Knowledge, Skills, & Abilities
- Knowledge of effective pedagogy, innovative learning methodologies across varied modalities, and best-practices in course and program curricular design and development.
- Knowledge extramural funding management, planning, proposal and budget development, and policy compliance.
- Knowledge of current trends in higher education teaching and research and emerging demographic trends.
- Effective verbal and written communication abilities.
- Ability to effectively work as part of a community of individuals from culturally diverse backgrounds.
- Ability to mentor students and teach a wide variety of courses across undergraduate and graduate levels.
Compensation Commensurate with experience. Annual salary commensurate with candidate's qualifications and related experience.
Submit your Application
Review of applications will begin on December 1, 2025. Vacancy will remain open until filled.
See the full position announcement and how to apply here.