Open Rank Professor- Tenure Track - Civil Engineering

FAC00235PO25

Open Rank Professor- Tenure Track - Civil Engineering

Columbia

College of Engineering and Computing

CEC Civil and Environmental Engineering

To commensurate with qualifications

Full Time

37.5

Full-time Equivalent (FTE)

9 months

Richland

Tenure-Track/Tenured

Faculty

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.

The University of South Carolina is committed to equal opportunity and proudly values the skills and experience military veterans bring to our workforce. Across South Carolina, we are making veterans a priority for employment and recognize their vital contributions to our state and our communities.

The Department of Civil and Environmental Engineering at the University of South Carolina in Columbia is seeking qualified applicants for a tenured or tenure-track faculty position in digital twins for civil infrastructure. The position is open-rank, with a preference for candidates at the Associate or Full Professor level.

Applicants should possess a Ph.D. in civil engineering or a closely related field by the start date of employment. They should have a demonstrated record of research accomplishments and a strong capacity for teaching undergraduate and graduate courses. Applicants at the senior level must also have a record of sustained excellence in teaching and research, including competitive external funding and interdisciplinary collaboration.

Successful candidates will be expected to develop internationally recognized, externally funded research programs in the field of digital twins. While all candidates will be considered, areas of particular interest include physics-based surrogate modeling, uncertainty quantification, and multi-modal sensing, especially as applied to civil engineering systems. The successful candidate will complement and expand the college’s existing expertise in digital twins, which includes AI-based modeling, decision-making interfaces, sensing technologies, drone data collection, and model updating. Candidates will be expected to teach in the department’s undergraduate and graduate programs and collaborate with researchers across the Molinaroli College of Engineering and Computing, including Electrical Engineering, Mechanical Engineering, the AI Institute, and the McNair Aerospace Center.

The University of South Carolina is designated as a “high research activity” university by the Carnegie Foundation. The Department of Civil and Environmental Engineering supports nationally competitive research and maintains state-of-the-art facilities in structural, geotechnical, water resources, environmental, transportation, and railway engineering.

Review of applications will begin in January 2026 and continue until the position is filled. Interested applicants should apply online athttps://uscjobs.sc.edu/postings/196822 with: (1) A cover letter indicating the main area of research, (2) A curriculum vitae, (3) A concise description of research plans, (4) A statement of teaching philosophy, and (5) Names and contact information of at least three references.

Applicants must possess a Ph.D. degree in civil engineering or a closely related field by the start date of employment, and a demonstrated record of research accomplishments. Applicants for the rank of Associate Professor and Full Professor must also have years of relevant academic experience commensurate with academic policy and a sustained record of excellence in teaching and research, including competitive funding and multidisciplinary collaborations.

Successful candidates will be expected to develop internationally recognized, externally funded research programs in digital twins applied to civil infrastructure. Preferred areas of expertise include surrogate modeling, uncertainty quantification, and multi-modal sensing. A record of collaboration in multidisciplinary teams is desirable.

08/16/2026

10/29/2025

Yes

Review of applications will begin in January 2026 and continue until the position is filled. Interested applicants should apply online at https://uscjobs.sc.edu/postings/196822 with: (1) A cover letter indicating the main area of research, (2) A curriculum vitae, (3) A concise description of research plans, (4) A statement of teaching philosophy, and (5) Names and contact information of at least three references.

Positions are advertised for a minimum of forty-five (45) business days on our job website. After forty-five (45) 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.

https://uscjobs.sc.edu/postings/196822

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.