Job Opportunities API

The Public Ledger of Openings

← Back to the ledger

Assistant Professor in Optimization

European Mathematical Society
CompanyEuropean Mathematical Society
CategoryEducation
LocationChapel Hill, North Carolina
Remote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
First seen3 Aug 2026 (the employer did not state a posting date)
Last verified11 Aug 2026
SourceThe employer's own careers page (company_site)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
Classification: Control Theory and Optimization The Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill has an opening for a tenure-track position in optimization at the assistant professor level starting July 1, 2023. The department is seeking candidates with a doctorate in a relevant field, strong training in mathematical optimization, and the potential to maintain a strong research program in this area. The successful candidates will be comfortable with teaching courses at both undergraduate and graduate levels in the department at the intersection of their expertise and the needs of the department. A commitment to application-oriented and interdisciplinary research, and to interaction with other groups in the department will be a positive factor in the consideration of candidates. The department and the university are committed to diversity, equity and inclusion, advancing the ideals espoused at https://diversity.unc.edu. We welcome applications from candidates who will add to the department’s diversity. We will begin considering candidates after November 1, 2022, 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, representative papers, and a graduate transcript. Applicants should also arrange for four letters of recommendation. At least one of the letters should include an evaluation of the applicant's teaching ability. Application materials and letters of recommendation must be submitted in electronic form only. For inquiries, please contact [email protected] The University is an equal opportunity, affirmative action employer and welcomes all to apply without regard to age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation or veteran status.