Faculty in Data Sciences - Critical Infrastructure...
Role details
Job location
Tech stack
Job description
The School of Data Science (https://www.odu.edu/datascience) at Old Dominion University invites applicants for an annual 10-month position at Assistant/Associate/Full Professor rank as part of a multi-position hiring cluster aiming for the Critical Infrastructure and Data Transformation to Advance National Security to begin in Fall 2026. This is an annual 10-month appointment that will begin July 25, 2026. The cluster, with faculty hires in School of Data Science, Batten College of Engineering and Technology and Office of Enterprise Research and Innovation, integrates interdisciplinary research in resilient infrastructure, infrastructure data transformation, and secure smart systems to address national security challenges in coastal regions. It explicitly addresses the Old Dominion University's Strategic Plan in research areas including Coastal Resilience and National Security. The research in this cluster will be supported by five interrelated, cross-cutting research domains, including Artificial Intelligence & Machine Learning, Computational & Data Science, Cybersecurity & Network Security, and Modeling & Simulation.
Candidates will be considered for appointment at all ranks contingent upon appropriate qualifications. 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 application on critical infrastructure and national security, including but not limited to, 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 ), Mason and Joan Brock Virginia Health Sciences ( VHS , formerly EVMS ), and ODU's Office of Enterprise Research and Innovation ( OERI ). https://www.odu.edu/datascience
Requirements
The appointee is expected to teach undergraduate and graduate courses and collaborate with other faculty in School of Data Science, Batten College of Engineering & Technology, and Office of Enterprise Research and Innovation. The appointee is encouraged to establish collaborations with the newly formed 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 Road Region.
Position Type FullTime
Type of Recruitment General Public
Type of Recruitment General Public
Minimum required education and/or special licenses, registrations, trainings, or certifications
A Ph.D. or equivalent in Data Science, Computer Science, Machine Learning, Engineering, Mathematics, or a closely related field is required.
Candidates applying for a senior faculty appointment (Associate Professor or Professor) must have academic records that merit a tenured appointment in the School of Data Science.
Minimum required level and type of experience, knowledge, skills, and abilities
Preferred Qualifications
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A strong publication record in data sciences/AI/ML.
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Strong record of externally funded grants.
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Excellent skills to interact and communicate clearly with internal and external constituencies