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 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.

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 equal opportunity 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.
• A deep understanding of traffic signal control and network optimization models.
• Proficiency in developing AI models for traffic control and optimization, including experience with spatiotemporal data, traffic network/graph analysis, and control signal data.
• Strong understanding of reinforcement learning algorithms (e.g., DQN, DDPG, PPO) and deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), graph neural networks (GNNs), Transformers, and the PyTorch ecosystem.
• Knowledge of deep learning theory, statistical modeling (e.g., decision trees, hidden Markov models, Kalman filters), and the ability to model partially observable complex dynamic systems.

Special Requirements:

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

Pease submit two letters of reference when applying for this position. You may upload these directly to your application or have them sent to Postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

Benefits at ORNL:

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous 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, and Employee Discounts.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email ORNLRecruiting@ornl.gov.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.