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

Oak Ridge National Laboratory • Knoxville, TN

27d

About The Position

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

The roles advance data-driven, AI-enabled mobility systems that connect vehicle-level automation with corridor- and regional-level transportation operations. Research includes developing, testing, and deploying connected-vehicle technologies and smart-infrastructure controls in real-world settings to improve mobility energy efficiency. Work may combine 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 for passenger, transit, and freight operations. Candidates need depth in one or more relevant areas and an interest in interdisciplinary collaboration; expertise in every area is not expected.

Appointments are for up to 24 months, with potential extension subject to performance and funding availability. Applicants must have received their Ph.D. no more than five years before applying and must complete all degree requirements before starting. Employment requires compliant identification and eligibility to obtain and maintain the required federal credential or, for eligible foreign national candidates who do not yet meet the U.S. residency requirement, a favorable site-specific risk determination. Two letters of reference are required with the application.

Requirements

• 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 must not have received their Ph.D. more than five years before the application date and must complete all degree requirements before starting the appointment.
• Demonstrated research experience in at least one relevant area: vehicle dynamics simulation; modeling and control of connected and automated vehicles; AI or machine learning for transportation; traffic modeling, control, routing, or optimization; transportation digital twins and simulation; vehicle energy modeling; heavy-duty vehicle operations; or intelligent transportation systems.
• Proficiency in Python and experience with at least one additional programming, modeling, or data-analysis environment such as C++, MATLAB, or Simulink.
• Experience developing computational models or data-driven methods and evaluating them using simulation, experimental, or real-world data.
• Strong analytical and problem-solving skills and ability to work independently and collaboratively in a multidisciplinary research environment.
• Excellent written and verbal communication skills, demonstrated through scholarly publications, technical reports, presentations, or comparable research products.
• Submit two letters of reference with the application.
• For employment, provide Real ID-compliant identification and be able to obtain and maintain a federal PIV credential following a favorable background investigation, or meet the applicable LSSO requirements for foreign national candidates who have not resided in the U.S. for three consecutive years.

Nice To Haves

• Experience with traffic simulation, vehicle simulation, or digital-twin platforms such as SUMO, VISSIM, Aimsun, CARLA, CarMaker, MATLAB, or Simulink.
• Experience with AI and machine-learning methods, including reinforcement learning, multi-agent systems, graph neural networks, spatiotemporal models, or Transformers, using PyTorch or a comparable framework.
• Experience applying LLMs, VLMs, or agentic AI to vehicle and infrastructure control, multimodal reasoning, scenario generation, planning, or transportation operations.
• Experience with traffic prediction, routing, signal control and priority, network optimization, or regional transportation operations, including systems and interfaces such as NTCIP, NEMA, SAE J2735, or ATMS.
• Experience integrating and analyzing multimodal transportation data, including trajectory, detector, video, LiDAR, connected-vehicle, transit, or fleet data.
• Experience with vehicle hardware, control-system integration, and cooperative driving automation, including software-, hardware-, or vehicle-in-the-loop testing, dynamometer evaluation, or on-road experiments.
• Knowledge of trustworthy AI, uncertainty quantification, safety guardrails, or evaluation under disruptive and out-of-distribution conditions.
• Experience developing reproducible research software and collaborating with public agencies, transportation operators, industry partners, or multidisciplinary research teams.

Responsibilities

• 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 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.
• Align behaviors, priorities, and interactions with ORNL's core values of Impact, Integrity, Teamwork, Safety, and Service, and promote equal opportunity through respectful workplace practices.

Benefits

• Medical and retirement plans
• Flexible work hours
• On-site fitness, banking, and cafeteria facilities
• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Vacation and holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree