Postdoctoral Research Associate in AI-Enabled Connected Vehicles and Smart Mobility Systems Oak Ridge National Laboratory in United States

Oak Ridge National Laboratory (ORNL) is recruiting a Postdoctoral Research Associate in AI-enabled connected vehicles and smart mobility systems in Knoxville, Tennessee, United States.

The Applied Research for Mobility Systems Group seeks highly motivated researchers to work on transportation artificial intelligence, digital twins, intelligent transportation systems, cooperative driving automation, and energy-efficient mobility. The role focuses on developing, validating, and demonstrating advanced mobility technologies using large-scale transportation data, high-fidelity simulation, vehicle-in-the-loop testing, and real-world field deployments.

Research topics include AI-ready datasets, predictive models, multimodal transportation data, vehicle and infrastructure control, eco-driving, signal control and priority, routing, resilient transportation operations, vehicle dynamics, energy models, and connected infrastructure. The position also involves integrating algorithms with simulation platforms, vehicle hardware, traffic control systems, and field demonstrations in collaboration with public agencies, transportation operators, universities, national laboratories, and industry partners.

Required background includes a Ph.D. in civil engineering, mechanical engineering, computer science, electrical engineering, industrial and systems engineering, operations research, robotics, data science, or a closely related field. Applicants should have research experience in at least one relevant area such as vehicle simulation, connected and automated vehicles, AI/ML for transportation, traffic modeling and optimization, transportation digital twins, vehicle energy modeling, heavy-duty vehicle operations, or intelligent transportation systems. Python plus one additional tool such as C++, MATLAB, or Simulink is required.

Preferred experience includes SUMO, VISSIM, Aimsun, CARLA, CarMaker, PyTorch, reinforcement learning, multi-agent systems, graph neural networks, spatiotemporal models, Transformers, LLMs/VLMs, traffic prediction, routing, signal control, NTCIP, NEMA, SAE J2735, ATMS, multimodal data analysis, and vehicle-in-the-loop or on-road experiments.

The appointment is up to 24 months with possible extension, subject to performance and funding availability. ORNL notes competitive pay and benefits, but no specific stipend amount is listed. Applicants must have completed the Ph.D. within the last five years and must finish all degree requirements before starting.

To apply, use the ORNL jobs portal and submit two letters of reference. References may be uploaded directly or emailed to [email protected] with the position title and requisition number in the subject line. For application issues, contact [email protected].