The Department of Educational Psychology in the College of Education at the University of Arizona invites applications for a tenure-track Assistant Professor in Human-Centered AI and Data Literacy, starting August 2027. We’re looking for a scholar at the intersection of education and information science who studies how people learn about, question, and use data and artificial intelligence in educational contexts.

The ideal candidate combines a deep understanding of how people learn, how information is organized and accessed, and how rigorous research produces reliable knowledge. They also understand how AI can improve learning, decision-making, and human performance in educational settings. They will connect theory and practice, turning advances in the learning sciences, cognitive science, data analytics, and AI into practical, ethical, and measurable solutions.

This is a joint appointment: 51% in Educational Psychology and 49% in the College of Information Science (InfoSci). Educational Psychology is a small, mentorship-focused department that does research and graduate training in learning and cognition, human development, motivation, measurement, and research methodology. It is growing its work in AI and data literacy, including fully online stackable certificates in Data Literacy in Education. InfoSci, an iSchools member, offers twelve degree programs and supports interdisciplinary research across data science, information science, and related fields.

The position is part of a university cluster hire, Developing the Human Intelligence Behind the Use of Artificial Intelligence. The cluster links Educational Psychology, Information Science, Cognitive Science, Public Health, and the Humanities. Its shared questions are about how AI and data-intensive systems can support better decisions and practices in education and human development. We especially welcome scholars whose work bridges basic and applied research.

Responsibilities include:

• Building an active, externally funded research program in human-centered AI, machine learning, causal inference, and/or learning analytics applied to education, health, or information systems
  Teaching four graduate and undergraduate courses per year across both units, online and in person
  Advising and mentoring master’s and doctoral students
  Building partnerships with P–16 schools, districts, and community colleges
  Collaborating across the cluster and contributing to department, college, university, and interdisciplinary service
  The workload is roughly 40% teaching, 40% research, and 20% service.

To apply: Submit a CV, a cover letter addressing your match to the criteria, a research statement, a teaching statement, three publications combined into one PDF, and contact information for three references. Review begins November 15, 2026; apply early for full consideration. Visa sponsorship is not available.

Apply at: https://arizona.csod.com/ux/ats/careersite/4/home/requisition/27551?c=arizona