The Department of City and Regional Planning (DCRP) in the College of Arts and Sciences and the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill invite applications for a Tenure Track, Assistant/Associate Professor position in Urban Analytics and Data Science. We seek outstanding individuals skilled in using data science to better understand cities and communities in North Carolina, the United States, or the world. We look for individuals creatively applying data science to all planning questions including the domains of transportation, economic development, real estate, and other areas. We are also interested in a broad array of analytic skills, particularly machine learning, network analysis, and spatial analysis.
This position is joint between City & Regional Planning and the Odum Institute. The selected individual will be expected to develop or extend a record of scholarly contribution as well as contribute to teaching and service in both units. Scholarly contributions will be demonstrated through development of a grant-funded research program along with publication of peer-reviewed research. Teaching and service contributions will involve leading courses for UNC's world-class undergraduates, graduate students, post-doctoral trainees, and faculty through the City and Regional Planning program and the Odum Institute. The selected individual will also provide a variety of research consultation services in machine learning, network analysis, and/or spatial analysis to the university community as well as contribute to grant-funded research of the UNC research community through their service as a data scientist at Odum.
Education and Experience:
The successful candidate will have strong capacity and willingness to teach and mentor at all levels, ideally demonstrated by previous experience.
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.
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