Postdoctoral Research Associate - Applied Research for Mobility Systems Group

Requisition Id 14088 

­­Overview:  

The Applied Research for Mobility Systems Group at Oak Ridge National Laboratory (ORNL) is seeking a motivated and highly skilled Postdoctoral Research Associate to contribute to cutting-edge research in mobility systems and intelligent transportation. The successful candidate will collaborate with a multidisciplinary team of researchers and engineers to develop innovative solutions that enhance the efficiency, safety, and sustainability of transportation networks.

 

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 7,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

 

Major Duties/Responsibilities: 

• Conduct data science and engineering practice for massive traffic data collection, processing, and fusion to generate AI-ready datasets.
• Develop and implement cutting-edge artificial intelligence (AI) models for traffic signal control and optimization, with a focus on decentralized reinforcement learning and spatiotemporal neural networks for real-time traffic management.
• Work closely with a multi-disciplinary team to conduct AI model training, testing, and validation in both simulated and real-world environments.
• Participate in field demonstrations and performance evaluations of AI-driven traffic control models, contributing to the successful deployment and scaling of these solutions.
• Publish high-quality research findings in peer-reviewed journals and present at conferences to contribute to the broader scientific community in transportation AI and optimization.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace – in how we treat one another, work together, and measure success.

 

Basic Qualifications:

• A Ph.D. degree in transportation engineering, computer science, mechanical engineering, electrical engineering, or a related field.
• Strong background in deep learning model development, computational modeling, traffic simulation, and data analytics.
• Advanced expertise in traffic engineering and traffic simulation tools (experience with APIs and/or SDKs of VISSIM, SUMO, or similar platforms) and the ability to work with real-world data.
• Proficiency in programming languages, such as Python, C++, or MATLAB.
• Proficiency in reinforcement learning techniques and familiarity with a range of deep learning models.
• Strong analytical and problem-solving skills with the ability to work both collaboratively and independently in a multidisciplinary research environment.
• Excellent verbal and written communication skills, with proven track record of scholarly publications and presentations.

 

Preferred Qualifications:

• Experience with real-time data processing and integration with traffic management systems.
• Prior experience with digital twin technologies or tools for traffic scenario generation and simulation.
• Strong knowledge and familiarity with National Transportation Communications for ITS Protocol (NTCIP) and National Electrical Manufacturers Association (NEMA) standards for traffic control systems.