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

Job in Columbia, Lexington County, South Carolina, 29228, USA
Listing for: Inside Higher Ed
Full Time, Part Time position
Listed on 2025-12-28
Job specializations:
  • Education / Teaching
    University Professor, Academic
Job Description & How to Apply Below
Location: Columbia

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

Posting Number
: FAC
00179PO23

Campus
:
Columbia

College/Division
:
College of Arts and Sciences

Department
: CAS Mathematics

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

Part/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 University Of South Carolina
:
From the Upstate to the Low country, 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.

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

Desired Start Date

08/16/2024

Job Open Date

10/03/2023

Open Until Filled

Yes

Special Instructions To Applicant

All applicants must apply at USCJobs () as well as via Math Jobs (https://(Use the "Apply for this Job" box below).). 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 Math Jobs. 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

/154173

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.

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