"Assistant Professor - Data-driven Modeling and Simulation of Complex Systems"

Job Details

Assistant Professor - Data-driven Modeling and Simulation of Complex Systems

University of South Carolina

Department: CAS Mathematics

Advertised Salary Range: We offer a competitive salary and benefits package.

Part/Full Time: Full Time

About UofSC

Diversity Statement

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

Special Instructions to Applicant: All applicants must apply at USCJobs at (https://uscjobs.sc.edu) as well as via MathJobs at (https://www.mathjobs.org). 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.

EEO Statement: The University of South Carolina does not discriminate in educational or employment opportunities on the basis of race, sex, gender, gender identity, transgender status, age, color, religion, national origin, disability, sexual orientation, genetics, protected veteran status, pregnancy, childbirth or related medical conditions.