Assistant Professor of Spatial Data Science
Posted: 9/26/2017 (Employment)
The University of California, Santa Barbara Department of Geography invites applications for a tenure-track position in spatial data science at the rank of Assistant Professor. The department seeks applicants with core research interests in inferential and computational analysis of spatial data, data mining, and machine learning in support of any substantive domain in the field of Geography or allied fields that rely on spatiotemporal data. The Department of Geography has strengths in three broadly defined areas: human geography; earth system science; and modeling, measurement, and computation. This position is most strongly associated with the third of these areas, but interest in one or both of the other systematic areas is also desirable. We provide opportunities for interactions with many other departments and research units on the campus, including the Center for Spatial Studies, various labs (Space and Time for Knowledge Organization, GeoTrans, GeoOpt), the Broom Demography Center, and the Center for Information Technology & Society. Preference will be given to candidates who have grounding in computational data analysis equivalent to, or exceeding, an M.S. in statistics, computer science, geoinformatics, or related fields, and will have a proven track record of collaboration with diverse disciplinary teams of scientists.To apply, please log in to https://recruit.ap.ucsb.edu/apply/JPF01091 to submit your cover letter, curriculum vitae, statements of research and teaching interests, and names of three referees with their contact information. A Ph.D in an appropriate field is required by the date of appointment. Applications completed by November 15, 2017 will receive priority consideration, but the position will remain open until filled. The effective start date of the position is July 1, 2018 or later.
The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching, and service.
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