Assistant Professor (Tenure-track)

The School of Data Science (SDS) (sds.charlotte.edu) is an interdisciplinary unit housed in the College of Computing and Informatics (CCI). The SDS, established in January 2020, was the first School of Data Science in the Carolinas. Currently, the School offers two Bachelor of Science degrees (Data Science and Sports Analytics), two Master of Science programs (Data Science and Business Analytics and Health Informatics and Analytics), and a PhD in Data Science. The SDS teaches and researches methods to apply statistics and computer science techniques to develop data-driven solutions to real-world problems. These areas vary from the ethical application and use of data to communication studies, business, healthcare, social sciences, transportation, engineering, and more. The school has grown quickly to more than 900 students, with half of them being graduate students, and is continuing to evolve with the needs of the students, university, and the community. Currently, the school has approximately 90 full-time, joint and affiliate faculty.

The College of Computing and Informatics (CCI) (cci.charlotte.edu) at UNC Charlotte is one of the most comprehensive and innovative computing colleges in the country. With over 140 faculty and staff and 5,000 students, CCI graduates more than 1,300 Bachelor's, Master's, and Ph.D. students a year. The College is organized into four academic units: Department of Computer Science (CS), Department of Software and Information Systems (SIS), Department of Bioinformatics and Genomics (BiG), and the School of Data Science (SDS). CCI has distinct research strengths in AI & Machine Learning, Cybersecurity & Privacy, Computational Bioinformatics & Genomics, Human-centered Design, High-Performance Computing and CS education. Located in Charlotte, the largest and fastest-growing city in the Carolinas, CCI engages with the community and neighboring industries around common social, research, and development initiatives.

The University of North Carolina at Charlotte recognizes the differentiation of mission, goals, and objectives inherent in the diversity of disciplines represented by its colleges and departments. Thus, the Job Responsibilities and Essential Functions for Tenured and Tenure Track Faculty should be interpreted in the context of the related departmental and collegiate goals.
Teaching, Advising, Curriculum and Instructional Development - Faculty responsibilities and essential functions with respect to teaching may include but are not limited to: subject matter competence, course design, course presentation, advising and consultation, directing student research, curriculum and instructional development, and grading student work.
Scholarly Research, Creative, and Other Professional Activities - All tenured and tenure-track faculty are expected to participate in expanding the knowledge base of their academic field by conducting research or engaging in other creative activities as appropriate to the faculty member's discipline. Faculty responsibilities and essential functions with respect to research may include but are not limited to: research/creative activity that generates new knowledge and/or synthesizes and/or integrates existing knowledge, publication, an on-going agenda for research, scholarly, and creative activity, and are expected to seek extramural support for their work.
Service to University, the Public, and the Profession - All tenured and tenure-track faculty are expected to engage in a program of service appropriate to their discipline. Faculty responsibilities and essential functions with respect to service may include but are not limited to: service to the administration and governance of the University, public service, and service to the profession.

To view the complete Job Responsibilities and Essential Functions for Tenured and Tenure-Track Faculty document visit our website: https://provost.charlotte.edu/academic-budget-hr/academic-personnel-procedures-handbook/

The qualified candidate is expected to focus on the broad area of machine learning or deep learning, particularly as it applies to domains such as business, social sciences, healthcare, or sports. Applicants who are able to address real-world challenges that intersect with organizational, behavioral, or technological systems, and go beyond algorithm development to explore social and community impacts of data-driven solutions, are of particular interest. The successful candidate will teach at both the undergraduate and graduate levels and will demonstrate a commitment to interdisciplinary research and collaboration.

UNC Charlotte gives primary consideration to the earned doctorate or terminal degree in the teaching discipline or a related discipline.

Applicants must have a Ph.D. in Machine Learning or a closely related field, such as Statistics, Data Science, Computer Science, or Information Science, by the start of their appointment. Applicants should demonstrate a strong potential for high-quality scholarly publications and promise in securing external research funding. Applicants should demonstrate an interest in teaching and curriculum development in data science at both the undergraduate and graduate levels and should have experience in data science applications. Preferred applicants are those who are genuinely enthusiastic about this faculty position and are eager to contribute to the teaching and research missions of the School of Data Science at UNC Charlotte.

N/A

Hiring is subject to budget availability

Applicants must submit the following materials through https://jobs.charlotte.edu/ (position number 003234):
* Cover letter
* Curriculum vitae
* Research statement
* Teaching statement
* Contact information for three professional references
* Up to three representative publications or manuscripts relevant to the position

Review of applications will begin on December 1, 2025, and will continue until the position is filled. Questions about the position may be directed to the Search Committee Chair, Dr. Michael Schuckers, at schuckers@charlotte.edu.

Final candidate subject to criminal background check.