Postdoctoral Research Associate in AI-Enabled Connected Vehicles and Smart Mobility Systems

The Applied Research for Mobility Systems Group at Oak Ridge National Laboratory (ORNL) is seeking highly motivated Postdoctoral Research Associates to conduct cutting‑edge research in transportation artificial intelligence, digital twins, intelligent transportation systems, cooperative driving automation, and energy‑efficient mobility. The selected candidates will work with multidisciplinary teams to develop, validate, and demonstrate advanced mobility technologies using large‑scale transportation data, high‑fidelity simulation, vehicle‑in‑the‑loop testing, and real‑world field deployments.

The positions will advance data‑driven and AI‑enabled mobility systems that connect vehicle‑level automation with corridor‑ and regional‑level transportation operations. A central emphasis will be developing, testing, and deploying connected‑vehicle technologies and smart‑infrastructure control in real‑world settings to improve the energy efficiency of mobility systems. The research will integrate multimodal transportation data, digital twins, vehicle dynamics and energy models, AI‑based control and optimization, connected infrastructure, vehicle‑in‑the‑loop and dynamometer testing, and field demonstrations to create scalable solutions for passenger, transit, and freight vehicle operations.

Candidates are not expected to have expertise in every area. We welcome applicants with strong depth in one or more relevant areas and interest in collaborating across disciplines. As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80‑year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals.

Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

• Develop AI‑ready datasets, digital twins, predictive models, and representative scenarios using multimodal transportation, vehicle, infrastructure, fleet, and energy data.
• Develop AI‑based control and optimization methods for connected vehicles and smart infrastructure, including eco‑driving, cooperative driving automation, signal control and priority, routing, and resilient transportation operations.
• Integrate research algorithms with vehicle and energy models, simulation platforms, vehicle hardware, connected infrastructure, and traffic control systems.
• Plan and conduct testing and evaluation through simulation, software‑and‑hardware‑in‑the‑loop, vehicle‑in‑the‑loop, dynamometer, and on‑road field experiments.
• Deploy and demonstrate research technologies in real‑world environments in collaboration with public agencies, transportation operators, national laboratories, universities, and industry partners.
• Evaluate impacts on energy efficiency, mobility, reliability, and resilience at the vehicle, corridor, and network levels.
• Produce reusable research software, datasets, models, evaluation tools, and deployment guidance; publish findings and present research at technical conferences.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace in how we treat one another, work together, and measure success.

• Ph.D. in civil engineering, mechanical engineering, computer science, electrical engineering, industrial and systems engineering, operations…