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Assistant Professor - Data-driven Modeling and Simulation

Job in Columbia, Richland County, South Carolina, 29204, USA
Listing for: College of Arts and Sciences
Full Time position
Listed on 2026-08-05
Job specializations:
  • Education / Teaching
    University Professor, Academic
Job Description & How to Apply Below

Assistant Professor - Data-driven Modeling and Simulation

The faculty of the Department of Mathematics at the University of South Carolina, Columbia campus, invites applications for a 9-month, full time, tenure-track position at the rank of Assistant Professor to begin August 16, 2025. The candidate is expected to contribute to synergistically bridging important developments in emerging mathematical foundations in Data Science and Artificial Intelligence and Modeling and 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.

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.

Applications must include: (1) a cover letter, (2) a curriculum vitae, (3) research statement, (4) teaching statement, and (5) the name and contact information for four references. Reference letters must be submitted through Mathjobs. Review of applications will begin on November 1, 2024 and continue until the position is filled. Please address inquiries to Dr. Qi Wang .

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.

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