About this opportunity
Statistics Interest Group lists this Open Rank - Fixed Term - (Assistant/Associate/Full) Teaching Professor opportunity in chapel hill, North Carolina. Review the employer’s description below for duties, qualifications and application requirements.
Job description
University of North Carolina – School of Data and Information Sciences – Open Rank – Fixed Term – (Assistant/Associate/Full) Teaching Professor
Position Title Open Rank - Fixed Term - (Assistant/Associate/Full) Teaching Professor
Company Information
The mission of DSS is to empower a diverse community of faculty conducting research in the fundamentals and/or the applications of data science. The Division is training undergraduate, graduate, and professional students to be the next generation of data science leaders with the knowledge and skills to thrive in this data-driven world. The Division will serve the state, the nation, and the world through premier data science educational programs and innovative research directed to advancing the public good with human centric and ethical applications.
The core elements of SDIS include porous borders: leveraging our low walled collaborative Carolina culture to solve major societal problems. Interdisciplinary research clusters that cross Division and School boundaries are a vital element of our Scholarly community. The School of Data and Information Sciences is focused on students and education – the emphasis is not just on data science majors but on all students becoming data literate. The school’s culture has an open and transparent structure, governance, and business model.
Duties and Responsibilities
The Division of Data Science and Society (DSS) in the School of Data and Information Sciences (SDIS) at the University of North Carolina at Chapel Hill invites applications for 9- or 12-month, fixed-term, open-rank (Assistant/Associate/Full) Teaching Professor in Data Science, with a focus on artificial intelligence, including the ethical, practical, and societal applications of AI tools. The position is to provide high-quality undergraduate instruction in data science and artificial intelligence while contributing to the continued development and expansion of the School’s data science and AI curriculum.
The successful candidate will teach courses such as DATA 117, DATA 317, and DATA 110 and will have opportunities to develop and teach new courses and learning experiences in AI and related areas. The position will contribute to the School’s ongoing expansion of data science and AI education by identifying emerging topics and instructional needs, developing innovative and accessible courses, and supporting curricular initiatives, including the AI minor launched in Fall 2026.
The successful candidate will collaborate across disciplines to ensure that course offerings reflect evolving AI methods, technologies, applications, ethical considerations, and societal implications.
We especially seek candidates with expertise or experience in:
Understanding how AI systems operate, including supervised learning, unsupervised learning, reinforcement learning, generative AI, and related approaches.
Ethical, legal, and societal considerations in data science and artificial intelligence, including data privacy, regulation, responsible AI, and responsible data use.
Making AI accessible to students with diverse technical backgrounds through engaging and inclusive undergraduate teaching.
Creating hands‑on learning experiences that apply AI to research, writing, data analysis, creative work, coding, and other academic and professional activities.
Teaching introductory data science or AI courses, particularly courses serving undergraduate and first‑year students.
Advising and mentoring a growing undergraduate student population.
The standard instructional assignment is three courses per semester for 9-month appointments (six courses annually) and four courses per semester for 12-month appointments (eight courses annually).
This is a permanent fixed‑term faculty position with an initial three-year appointment, subject to reappointment, and a pathway for advancement in rank.
Position Qualifications
Minimum Education and Experience Requirements
A PhD or equivalent terminal degree in data science, computer science, information science, statistics, a social science, humanities discipline, or another substantive field relevant to the mission and academic programs of the Division of Data Science and Society.
Preferred Qualifications, Competencies, and Experience
Demonstrated experience teaching at the college or university level, with experience in data science, artificial intelligence, or a related field.
Knowledge of artificial intelligence and machine learning concepts, including supervised learning, unsupervised learning, reinforcement learning, generative AI, and related methods.
Experience applying AI tools to research, writing, data analysis, creative work, coding, or other academic and professional contexts.
Demonstrated ability to advise and mentor undergraduate students.
Ability to collaborate effectively with faculty and colleagues across disciplines in an interdisciplinary academic environment.
#J-18808-Ljbffr
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.