Position Summary
The School of Education at the University of North Carolina at Chapel Hill invites applications for up to two positions in the Learning Sciences starting July 1, 2018. These are full-time, 9-month tenure-line or tenured appointments depending on rank at the time of hire. Candidates with distinguished scholarly records and established national/international leadership and reputation will be eligible for consideration for named professorships.
Context: The University of North Carolina at Chapel Hill (Carolina), established in 1793 as the first public university in the nation, is a doctoral-granting institution situated in the beautiful college town of Chapel Hill, NC. Ranked fifth among public institutions by US News & World Report, and one of the original public ivy schools, Carolina has earned a reputation as one of the best universities in the world. We pride ourselves on a strong, diverse student body, unparalleled academic opportunities, and a value unmatched by any public university in the nation. The School of Education is among the best in the nation, and boasts a rapidly growing program in the learning sciences.
Responsibilities
Candidates will carry out a research program, actively pursue external funding, and contribute to collaborative and interdisciplinary research and instructional efforts across the School of Education and campus. Candidates also will (a) develop and teach undergraduate and graduate courses in the learning sciences and related areas delivered in face-to-face, online, and/or blended formats; (b) contribute to the ongoing development of undergraduate and graduate programs; (C) actively recruit and supervise graduate students; (d) support strategic initiatives across the School and campus; and (e) provide leadership and service at the local, state, and national levels.
The positions require a clear and characteristic focus on cutting-edge digital ecologies for teaching and learning (virtual and augmented realities; serious gaming; immersive technologies that enable adaptive-personalized experiential learning opportunities and interventions; etc.), and/or the application of data mining, data analytics, natural language processing, or adaptive assessment—among other emerging fields—to massive datasets (i.e., big data) to address difficult educational challenges. Candidates’ work within these ecologies could address the various content areas (STEM, literacy, etc.), as well as measurement, assessment, and/or evaluation.
Qualifications
Candidates at the Assistant Professor level must have an earned doctorate at the time of hire. Candidates at the Associate and Full levels must have an established record of research, funding, teaching, and service to meet the University’s requirements for tenure and appointment at the respective rank. Depending on rank, 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.
Salary and Starting Date
Salary will be competitive and commensurate with rank and experience. The proposed starting date is July 1, 2018.
The Application Process
To apply for the position, submit a letter of interest, vita, and the names of four references with full contact information, using the online application process at http://unc.peopleadmin.com/postings/126446.
For full consideration, all application materials should be received by October 10, 2017 at which time the search committee will begin reviewing applications. The search will remain open until filled.
For more information, email the Search Chair, Jeff Greene, jagreene@email.unc.edu
The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or status as a protected veteran.