Title: Faculty in Data Science (Tenure Track/Tenured, Position # F1050A)
Agency: ACADEMIC AFFAIRS
Location: Norfolk, VA
FLSA:
Hiring Range:
Full Time or Part Time:
Job Description:
The School of Data Science at Old Dominion University invites applicants for an open rank (Assistant/Associate/Full) as part of a multi-position hiring cluster aiming for the AI-Infused Autonomous Systems for Medicine and Health to begin in Fall 2026. This is a tenured/tenure-track, 10-month appointment that will begin July 25, 2026. Candidates will be considered for appointment at all ranks contingent upon appropriate qualifications. The cluster, with faculty hires in the School of Data Science, Batten College of Engineering and Technology, and Hampton Roads Biomedical Research Consortium (HRBRC), integrates interdisciplinary research in secure data infrastructure, real-time sensing, and trustworthy analytics to support autonomous decision-making across hospitals, clinics, and remote care settings.
We seek faculty that to develop/maintain a vibrant, externally funded interdisciplinary research program in artificial intelligence (AI)/machine learning (ML) and data science with a primary focus on connected and autonomous systems for healthcare, including but not limited to: Privacy-Preserving Federated Learning for In-Hospital Sensor Networks
Digital-Twin–Driven Hospital Flow Optimization
Trust and Explainability in Autonomous Diagnostics
Adaptive Multi-Modal Sensing for Remote Patient Monitoring
Large-Scale Health Data Infrastructure for Autonomous Systems
AI-Enhanced solutions
Cyber-Physical Security for Medical Autonomy
Streaming Data Fusion and Synchronization for Medical Autonomous Systems
Connected Autonomous Systems for Emergency Response and Disaster Relief The focus of this cluster is to leverage cutting-edge data science and artificial intelligence to transform healthcare delivery across hospitals, clinics, especially in underserve communities. The research of this cluster is expected to deliver innovative, data-driven methods and autonomous technologies that expand high-quality healthcare into medically underserved areas, enhance hospital efficiency, and ensure secure, reliable care across diverse clinical environments.
The appointee is expected to teach undergraduate and graduate courses and collaborate with other faculty in the School of Data Science, Batten College of Engineering & Technology, and Hampton Roads Biomedical Research Consortium. The appointee is encouraged to establish collaborations with the newly formed Macon & Joan Brock Virginia Health Sciences, as well as scientists at the nearby federal research facilities such as Thomas Jefferson National Accelerator Facility (Jefferson Lab), NASA Langley Research Center (LaRC) and Navy Surface Warfare Center in the Hampton Roads Regione. About the School of Data Science: As one of the three academic units in the Interdisciplinary Schools at Old Dominion University, the School of Data Science is a new initiative that focuses on educating students in the rapidly growing field of data science, conducting cutting-edge research and serving as a center of AI education and research in the University community. Since its establishment in spring 2023, the school has grown to include ten core faculty members and over 80 affiliated faculty members across the campus, with wide range of active research projects from bioinformatics, web science, survey data science to scientific machine learning, explainable AI and generative AI. Faculty of the School of Data Science actively collaborate with researchers from renowned facilities such as Jefferson Lab (sponsored by Department of Energy), NASA’s Langley Research Center, Hampton Roads Biomedical Research Consortium (HRBRC), Macon and Joan Brock Virginia Health Sciences (VHS, formerly EVMS), and ODU’s Office of Enterprise Research and Innovation (OERI).
Minimum Qualifications:
Additional Considerations:
A strong publication record in data science/AI/ML.
Strong record of externally funded grants
Excellent skills to interact and communicate clearly with internal and external constituencies.
