Careers
Assistant Professor
Description of Duties
Faculty in this position are expected to:
Conduct innovative, externally funded research in applied artificial intelligence and machine learning.
Teach undergraduate and graduate courses in AI and its applications, contributing to curriculum development.
Collaborate with faculty across disciplines to integrate AI into real-world application domains such as precision agriculture, sustainability, manufacturing, and infrastructure.
Advise and mentor students at the undergraduate, master’s, and doctoral levels.
Engage in professional and institutional service, including outreach, committee participation, and strategic initiatives.
Actively contribute to the goals of the Institute for Applied Practice in AI and Machine Learning and promote NMSU’s role as a leader in AI innovation for the state and region
Education: Earned Ph.D. in a field relevant to artificial intelligence or machine learning by the time of hire.
Experience:
Evidence of scholarly productivity in AI or machine learning.
Demonstrated commitment to excellence in teaching and student mentoring.
Strong potential (or demonstrated record) for obtaining external research funding.
Additional Qualifications:
Ability to work effectively in a collaborative, multidisciplinary academic environment.
Preferred experience includes engagement with industry/government, responsible AI practices, and support of diverse student populations.
Knowledge, Skills and Abilities
Knowledge: Advanced understanding of artificial intelligence and machine learning techniques and their application across domains.
Skills: Ability to conduct independent research and produce scholarly outputs in AI or related fields.
Abilities: Integrate AI into applied domains such as agriculture, advanced manufacturing, and supply chain systems.
Teaching & Curriculum Development
Knowledge: Familiarity with modern instructional techniques in AI and interdisciplinary teaching approaches.
Skills: Capable of developing and delivering engaging undergraduate and graduate courses.
Abilities: Design curricula that integrate real-world AI applications and mentor diverse student populations.
Collaboration & Innovation
Knowledge: Understanding of interdisciplinary research practices and team-based science.
Skills: Effective communication and collaboration across academic and industry stakeholders.
Abilities: Build and sustain productive partnerships and research networks within and beyond the university.
Student Success & Service
Knowledge: Academic advising practices and student support strategies.
Skills: Mentorship of students at all levels in research and career development.
Abilities: Foster inclusive learning environments and support institutional goals of student success and engagement.