Faculty in Data Sciences - Critical Infrastructure and Data Transformation (CID) to Advance National Security

Commonwealth of Virginia
Norwich
4 months ago
Create job alert

Title: Faculty in Data Sciences - Critical Infrastructure and Data Transformation (CID) to Advance National Security

Agency: ACADEMIC AFFAIRS

Location: Norfolk, VA

FLSA:

Hiring Range:

Full Time or Part Time:


Job Description:
The 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: AI-Enabled Digital Twins for Critical Infrastructure or Coastal Resilience
Edge Intelligence for autonomous sensing and decision making
Secure & Trustworthy AI
AI-Driven Resilience Forecasting for Critical Assets
Human - AI Decision Support
AI for cyber-physical threat detection and response
Foundation Models for Integrated National-Security Intelligence and coastal resilience The focus of this cluster is to leverage cutting-edge data science and artificial intelligence to protect critical assets and strengthen national security, particularly in the coastal regions. The research of this cluster is expected to advance research that enable earlier warnings, faster responses, and greater resilience to both natural hazards and national security threats.
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.
Minimum Qualifications:

Additional Considerations:


A strong publication record in data sciences/AI/ML.
Strong record of externally funded grants.
Excellent skills to interact and communicate clearly with internal and external constituencies

Related Jobs

View all jobs

Data Science Faculty of Data-Driven AI in Special Education (Tenure Track/Tenured, F1051A)

Faculty in Data Science (Tenure Track/Tenured, Position # F1050A)

Faculty Fellowship Programme - Data Science - May 2026

Faculty in Applications of Physics, Data Science and/or Engineering to Particle Accelerators (Tenured, F1117A

Teaching Associate - Data Science / Statistics

Senior Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.