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Big Data/Computational Social Science, Assistant Professor, Associate Professor, or Full Professor, University of Oklahoma, Norman, OK

Open Rank, Open Department Big Data/Computational Social Science Faculty Position

Open Date: Oct 15, 2018; Application Link:

The College of Arts and Sciences at the University of Oklahoma invites applications from energetic, enterprising Big Data/Computational Social Science scholars for an open rank, tenured/tenure track faculty position. This search is part of a cluster hire in the new Data Scholarship Program (DSP).

The DSP is designed to support data science, data analytics, statistics, computational social science, and digital humanities across the university community. This position will play an integral role in the growth and development of the DSP.

Candidates from a broad range of social science and social science-related disciplines are encouraged to apply (including, but not limited to: African and African-American Studies, Anthropology, Communication, Economics, Library and Information Studies, Native American Studies, Political Science, Psychology, Social Work, and Sociology).

The position will begin in August 2019. The teaching load will be dependent upon the usual teaching load of hiring department.

The successful candidate is expected to become a leader within a highly collaborative interdisciplinary research and teaching community. We are looking for a social scientist doing innovative work (i.e., machine learning, text analysis, network analysis, data visualization, etc.) and/or utilizing novel datasets (linked, messy, unstructured, in-the-wild, real-time, or based on novel collection methods) that will magnify existing OU strengths. The ideal candidate should be fluent in emerging areas of Big Data social sciences, such as high-dimensional models and the use of "online field experiments;" acquiring "data in the wild" or using unconventional data sources to investigate human behavior or perceptions; and/or developing innovative data collection techniques or statistical methods. Successful candidates will be expected to apply for extramural funding, including participating in collaborative proposals, such as from the DoD, NSF, and NIH, and private sources.

This hire will address critical needs of OU students for additional training in data analytics and data-driven research, from introductory to advanced levels, to meet the high and growing demand for a work force with data-related skills, particularly those who can ground their analyses in core areas of interest to social scientists. We are looking for teaching expertise in the areas of: basic computing for social scientists, advanced courses in the substantive domain of the candidate, and courses in quantitative analyses and statistical methodologies.

Required Qualifications

  • A doctoral degree in a social science or any related discipline.
  • An established, active, and productive research program.
  • Experience with computational tools and/or "Big Data" methods for analyzing and/or visualizing data.

Preferred Qualifications

  • Knowledge and skills essential to Big Data/computational social science project development and completion, including but not limited to skills related to developing and managing large or non- conventional datasets, machine or statistical learning and/or causal inference, data analysis and visualization, and/or mining textual, visual, or aural data.
  • Evidence of excellence in teaching that engages students in Big Data/computational social science skill development.
  • Application of large datasets or data science methods to address questions of interest in the social sciences.
  • A sustained research program and a record of top-tier, peer-reviewed or other high-impact scholarly publications.
  • Experience with collaborative, cross-disciplinary research and a record of extramural funding.
  • Leadership in research, instruction, and/or service.

The salary is competitive and commensurate with qualifications and experience. The University of Oklahoma offers an excellent benefits program. For further information please access the Human Resources website at

The University of Oklahoma (OU) is a Carnegie-R1 comprehensive public research university known for excellence in teaching, research, and community engagement, serving the educational, cultural, economic and health-care needs of the state, region, and nation from three campuses: Norman, Health Sciences Center in Oklahoma City and the Schusterman Center in Tulsa. OU enrolls over 30,000 students and has more than 2700 full-time faculty members in 21 colleges. In 2014, OU became the first public institution ever to rank #1 nationally in the recruitment of National Merit Scholars, with 311 scholars and now boasts a 92% student retention rate. The University is home to the Carl Albert Center, the Center for Applied Social Research, the Center for Risk and Crisis Management, the National Institute for Risk and Resilience, and renowned natural history and art museums. The 277-acre Research Campus in Norman was named the No. I research campus in the nation by the Association of Research Parks in 2013. The University of Oklahoma's beautiful, bustling campus is nestled in the heart of Norman, the state's third largest city, located just south of Oklahoma City. Norman combines the charm of a college town, the sophistication of a cosmopolitan city and the history and culture of the American West. With outstanding schools, amenities, and a low cost of living, Norman is a perennial contender on the "Best Places to Live" rankings. With a cost of living close to 15 percent less than the national average, Norman is a very affordable city. In fall 2014, Time ranked Norman the "least expensive city to raise children." For more information visit: and

Application Instructions Applications should be submitted to on ByCommittee and should include a cover letter, curriculum vitae; three letters of reference; a statement of research interests and how the candidate would contribute to research and teaching in the development of a data scholarship program.

Review of applications will begin November 15, 2018, and will continue until the position is filled.

Questions about the position may be directed to the chair of the search committee, Dr. Carol L Silva at

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