Assistant Professor in Data Science

The University of North Carolina-Chapel Hill (UNC Chapel Hill) aims to contribute to the burgeoning field of data-oriented modeling and analysis, to solve pressing problems in healthcare, business, transportation, engineering, and other domains, and to study the implications of the usage of data science tools on society at large. The School of Data Science and Society (SDSS) will also be developing a core curriculum for training the next generation of data scientists at the undergraduate and graduate level. Given the highly interdisciplinary nature of this field, the SDSS and the College of Arts and Sciences (CAS) of UNC Chapel Hill are planning a cluster hire to attract outstanding tenure track faculty whose research and teaching interests lie at the intersection of data science and Mathematics (MATH), Statistics & Operations Research (STOR), or Computer Science (CS). These joint hires will have their tenure homes in SDSS but depending on their core area of expertise, will hold a half-time appointment in the MATH, STOR, or CS Department and contribute to their teaching and research mission as well. New hires will be helping to build undergraduate and graduate programs with a strong quantitative core as well as many interdisciplinary options. As a part of this overarching initiative to deepen and expand research and teaching related to data science, applications are invited at the rank of Assistant Professor – with a starting date of July 01, 2024. The STOR department is organized around four areas: theoretical and applied statistics; probability; stochastic modeling; and optimization. Faculty in the department conduct fundamental research in these areas and have many collaborations with other parts of UNC including health care, medicine, public health and environmental sciences. The ideal candidate for this position would be someone with primary expertise in one of the STOR department’s core areas, at the intersection with data science including machine learning, and potential for developing significant collaborations with the SDSS. Consistent with current SDSS themes, candidates with some background in machine learning / artificial intelligence or health care applications are particularly urged to apply. While the position itself will be joint, the tenure home will be SDSS. Candidates must possess a PhD in Statistics, Operations Research, or some closely related field by the start date of the appointment. Applicants are also expected to have a strong track record in research, teaching, and service commensurate with the level of the appointment. The successful candidate will be expected to direct an independent research program supported by extramural funding, to participate in data science activities and to teach at the undergraduate and graduate levels through the STOR department and SDSS. We will begin considering candidates after November 3, 2023, and will continue accepting applications until the position is filled. The application package should include a cover letter, an up-to-date curriculum vitae, research and teaching statements and representative papers. Candidates should include a graduate transcript and arrange for four letters of recommendation, at least one of which should include an evaluation of the applicant's teaching ability. Application materials and letters of recommendation must be submitted in electronic form only; click on https://unc.peopleadmin.com/postings/266959 to apply for this position. For further information on SDSS or the STOR department, please visit https://datascience.unc.edu and https://stor.unc.edu, or contact the faculty search committee at Stor-Search-SDSS24@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.

Last updated: 25 October 2023