Assistant Teaching Professor, Industrial and System Engineering Department

Tenure-Track Assistant Professor:
Position 004416

The Industrial and Systems Engineering Department (ISE) at UNC Charlotte is seeking candidates for a 9-month tenure-track Assistant Professor (Pos 4416) with an expected start date of August 2027. A successful candidate will teach undergraduate and graduate courses in engineering management (e.g., project management, supply chain management), systems engineering, operations research, data analytics, and artificial intelligence applications; contribute to curriculum development;

and mentor undergraduate and graduate students. The candidate is expected to establish and maintain an active, high-impact, and externally funded research program that complements and supports multidisciplinary research efforts in healthcare, manufacturing and supply chains, energy, and transportation and advanced mobility.

Research expertise may include systems modeling and decision analysis, forecasting, machine learning, optimization, reliability, simulation, and related analytical and computational methods. The department is particularly interested in candidates who leverage artificial intelligence, machine learning, big data, cloud/edge computing, cybersecurity, and related emerging technologies to address contemporary engineering management and systems challenges. Potential application areas include transformational energy systems and digital twins for energy applications;

intelligent vehicles, electrification, and large-scale transportation systems; healthcare systems and technologies; digital manufacturing, smart manufacturing, and resilient supply chains; and smart and sustainable cities and infrastructure. Candidates may also develop research that bridges multiple application areas, such as intelligent transportation and energy systems, digital twins for manufacturing and healthcare, or data-driven optimization of interconnected infrastructure.

The candidate will be expected to disseminate research through peer-reviewed journal publications and national and international conferences and to pursue external funding to develop and sustain a productive research program. The candidate is also expected to contribute to multidisciplinary research collaborations within the department, college, university, and external organizations. The candidate will participate in service activities within the department, college, and university, as well as in relevant professional engineering organizations.

Engagement with industry partners and regional stakeholders is expected to strengthen collaborative research, support educational and workforce development initiatives, and enhance the impact of the department’s teaching, research, and service missions.

Applicants must hold a Ph.D. degree in Engineering or another closely related field, such as Operations Research and Applied Mathematics. Preferred applicants will have a background in systems analytics and its applications in one or more of the following areas: supply chain, health care, transportation, energy, and manufacturing, and can teach R and Python. In addition, they must demonstrate significant accomplishments or outstanding potential in scholarship, teaching, and research, depending on the rank of appointment.

Successful candidates are expected to:

Complete applications must include a current resume; a letter of interest; one page statement of research; one page statement of teaching; and the names, addresses, telephone numbers, and e-mail addresses for three professional references. Review of applications will begin 11/16/2026.

The ISE program offers a dynamic undergraduate experience grounded in analytics, optimization, systems design and real-world problem solving, capped with hands-on industry projects. High-achieving students can accelerate their path through Early Entry graduate coursework. At the graduate level, flexible master’s options, including Engineering Management, prepare professionals to lead technical teams, improve processes and drive data-informed decisions across industries.