The University of North Carolina-Chapel Hill (UNC Chapel Hill) has established a School of Data Science and Society (SDSS) in 2022. This new school 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 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 the MATH, STOR, or CS Department in the CAS, depending on their core area of expertise, but will hold a half-time appointment at SDSS 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 being invited at Assistant or Associate Professor rank with a starting date of July 01, 2023. For further information on SDSS or the STOR department, please visit
https://datascience.unc.edu and
https://stor.unc.eduThe 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. This position is tenure track Assistant or Associate Professor position. 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. While the position itself will be joint, the tenure home will be STOR. 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.
Minimum Education and Experience Requirements 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 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.
We will begin considering candidates after January 15, 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 at the Assistant Professor level should also 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. Candidates for an Associate Professor position should submit names of four individuals who are willing to write letters if asked. Questions should be directed to the Search Committee at
stor-search-sdss@office.unc.edu.
Link to job posting:
https://unc.peopleadmin.com/postings/247369------------------------------
Richard Smith
University of North Carolina
------------------------------