The University of North Carolina at Chapel Hill's School of Education is seeking a faculty member to conduct cutting-edge, theory-grounded research in how to leverage artificial intelligence techniques to design and implement tools and solutions that enhance K-12 learning, teaching, and/or administration.
Requirements
- expertise in the development of machine learning and/or learning analytics solutions
- experience translating that expertise into practical, useful, and scalable solutions for enhancing teaching, learning, and/or the administrative structures that facilitate teaching and learning in K-12 settings
- research focus on developing tools and/or solutions that leverage large datasets and theory to improve learning, teaching, and/or administration in education
Responsibilities
- design and implement tools and solutions that enhance K-12 learning, teaching, and/or administration
- development of machine learning and/or learning analytics solutions
- translating that expertise into practical, useful, and scalable solutions for enhancing teaching, learning, and/or the administrative structures that facilitate teaching and learning in K-12 settings
- developing tools and/or solutions that leverage large datasets and theory to improve learning, teaching, and/or administration in education
Other
- Candidates must hold a doctorate in Education, the Learning Sciences, Educational Psychology, Educational Data Science, Artificial Intelligence in Education, or related disciplines.
- Candidates at the Assistant Professor level must have an earned doctorate at the time of hire.
- Candidates at the Associate Professor level must have an established record of research, funding, teaching, and service to meet the University’s requirements for tenure and appointment.
- Candidates will demonstrate a research program that will lead to an outstanding and sustained record of scholarship and securing external funding or will already have such an established record.
- Candidates will have strong potential, or an established record, of outstanding university teaching and guiding students through dissertation research projects.
- submit a letter of interest, vita, and the names of four references with full contact information, using the online application process
- For full consideration, all application materials should be received by October 1, 2025
