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Assistant Professor - Data-driven Modeling and ...

The University of South Carolina - Columbia, SC

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Job Description

Posting Details Posting Summary LogoPosting Number FAC00179PO23 Advertised Title Assistant Professor - Data-driven Modeling and Simulation of Complex Systems Campus Columbia College/Division College of Arts and Sciences Department CAS Mathematics Advertised Salary Range We offer a competitive salary and benefits package. Location of VacancyPart/Full Time Full Time Hours per Week 40 Position Category Full-time Equivalent (FTE) Basis 9 months Work County Richland Tenure Information Tenure-Track/Tenured Job Search Category Faculty About USC About University of South Carolina From the Upstate to the Lowcountry, the University of South Carolina system is transforming the lives of South Carolinians through the impact of our eight institutions and 20 locations throughout the state. More than 50,000 students are enrolled at one of eight institutions, including the research campus in Columbia and comprehensive four-year universities in Aiken, Upstate and Beaufort. In addition, our Palmetto College campuses in Salkehatchie, Union, Lancaster and Sumter enable students to earn associate or bachelor's degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service - helping to build healthier, more educated communities in South Carolina and beyond. Veterans' Preference Statement Benefits for FTE Positions The University of South Carolina (USC), through the State of SC and Public Employee Benefit Authority (PEBA), offers state employees a valuable benefits package, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at Position Description Advertised Job Summary The Department of Mathematics at the University of South Carolina is inviting applications for two 9-month tenure track Assistant Professor positions in data-driven modeling and simulation of complex systems. The candidate is expected to contribute to synergistically bridging important developments in emerging mathematical foundations in Data Science and Artificial Intelligence and numerical simulation of complex systems. A successful candidate is expected to teach at all levels in the Department of Mathematics, and to participate actively in the state-wide NSF-funded EPSCOR project on AI-enabled Devices for the Advancement of Personalized and Transformative Healthcare in South Carolina. Required Education and Experience Candidates must have a Ph.D. in Mathematics by the start date of employment, an outstanding research record, a commitment to effective teaching at the undergraduate and graduate levels, and a demonstrated potential for excellence in both research and teaching. Preferred Qualifications Ph.D. in Mathematics Posting Detail Information Desired Start Date 08/16/2024 Job Open Date 10/03/2023 Job Close DateOpen Until Filled Yes Special Instructions to Applicant All applicants must apply at USCJobs at (as well as via MathJobs at (A completed application will include a cover letter, curriculum vitae, description of research plans, and statement of teaching philosophy. In addition, four letters of recommendation should be made available through MathJobs. One of the letters should appraise the candidate's teaching ability. Positions are advertised for a minimum of five (5) business days on our job website. After five (5) business days, positions can be closed at the discretion of the department at any time. This position is open until filled. This employment site is updated on a regular basis. The length of the recruitment and screening process may vary from position to position, depending upon a variety of factors. Should review of your qualifications result in a decision to pursue your candidacy, you will be contacted by phone or email. Quicklink for Posting EEO Statement The University of South Carolina does not discriminate in educational or employment opportunities or decisions for qualified persons on the basis of age, ancestry, citizenship status, color, disability, ethnicity, familial status, gender (including transgender), gender identity or expression, genetic information, HIV/AIDs status, military status, national origin, pregnancy (false pregnancy, termination of pregnancy, childbirth, recovery therefrom or related medical conditions, breastfeeding), race, religion (including religious dress and grooming practices), sex, sexual orientation, veteran status, or any other bases under federal, state, local law, or regulations.

Created: 2026-03-10

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