R&D Associate Staff - Applied Research for Mobility Systems

Oak Ridge National Laboratory; Knoxville (TN); On-site; USD 90,000 - 130,000; Full time

Job summary

Oak Ridge National Laboratory (ORNL) invites applications for an R&D Associate Staff in the Applied Research for Mobility Systems (ARMS) Group. You will advance VIL/HIL testing, integrate vehicle and sensor systems, and apply AI to generate realistic vehicle scenarios and evaluate energy, safety, and performance.

The role emphasizes real-time simulation, experimental integration, and collaboration across multidisciplinary teams in a national lab setting.

Qualifications

• Ph.D. in Mechanical Engineering, Automotive Engineering, Electrical Engineering, Computer Engineering, Robotics, or related field.
• At least 1 year of relevant research or professional experience in vehicle systems, connected and automated vehicles, ADAS, controls, robotics, or transportation systems.
• Experience with real-time simulation and testing environments (VIL/HIL/SiL).
• Proficiency in Python and MATLAB/Simulink for modeling, data processing, and experimental control.
• Experience applying AI or data-driven methods such as deep learning, computer vision, time-series analysis, or sensor fusion.
• Ability to develop and integrate experimental hardware and software systems.
• Strong writing and communication skills for reports and proposals.

Responsibilities

• Develop standardized testing and evaluation methods for connected and automated vehicle technologies.
• Design vehicle-in-the-loop and hardware-in-the-loop experiments with production vehicles, dynamometers, and sensor systems.
• Develop closed-loop control and validation methods to reflect real-world behavior.
• Apply AI and generative methods to create realistic vehicle trajectories and edge-case scenarios.
• Build scalable vehicle and traffic simulation and data-analysis tools in Python, MATLAB/Simulink, and CARLA/SUMO.
• Lead experimental planning and coordinate with facilities, vendors, and partners.
• Document methods and contribute to proposals, reports, and publications.

Skills

Python

MATLAB/Simulink

C/C++

Machine learning

AI for scenarios

Real-time simulation

Vehicle dynamics

Sensor fusion

R&D collaboration

Education

Ph.D. in Mechanical Engineering or related field

Tools

dSPACE

CARLA

SUMO

Job description

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R&D Associate Staff - Applied Research for Mobility Systems

The Applied Research for Mobility Systems (ARMS) Group at Oak Ridge National Laboratory (ORNL) is seeking applicants for an R&D Associate Staff position focused on connected and automated vehicles, advanced driver assistance systems, vehicle-in-the-loop simulation, and artificial intelligence for transportation. The successful candidate will develop testing, simulation, and data-driven methods to evaluate the energy, safety, and operational performance of emerging vehicle technologies. Key activities include advancing VIL and HIL capabilities, integrating vehicle and sensor systems, developing standardized test procedures, and applying AI to scenario generation and system evaluation. The ideal candidate will have a strong background in vehicle systems and controls, real-time simulation, experimental integration, and artificial intelligence.

The ARMS group is within the Vehicle and Mobility Systems Research (VMSR) Section of the Buildings and Transportation Science Division (BTSD). The VMSR Section focuses on accelerating the development of advanced vehicles and complex mobility systems through advances in connected and autonomous vehicle technologies, communications, systems integration, and decision science. The objective of the ARMS Group is to provide leadership in advanced anything-in-the-loop research to accelerate the development of transportation technologies from component-level to full vehicles to traffic networks.

Research in ARMS group includes:

• Identify, collect, and process real-world data, such as road network information (geographic information systems data), traffic density and flow, signal timing plan, fleet population mix, routing, etc., and develop realistic scenarios in traffic microsimulation software and virtual environment/vehicle simulators.
• Establish detailed light-duty (LD), medium-duty (MD), and/or heavy-duty (HD) vehicle models with emerging mobility technology capabilities, such as connected and automated vehicles (CAVs), cooperative driving automation (CDA), and electrified vehicles. Develop simulations of these vehicles operating in diverse traffic, geographies, and environments to assess impact of emerging mobility technologies on the transportation system.
• Development and implementation of advanced software-in-the-loop (SIL) and hardware-in-the-loop (HIL) systems to support advanced powertrain, CAV and CDA control system design, validation, and verification.

Major Duties/Responsibilities:

• Develop standardized testing and evaluation methods to quantify the energy, safety, and operational performance of connected and automated vehicle and ADAS technologies.
• Design and conduct vehicle-in-the-loop and hardware-in-the-loop experiments that integrate production vehicles, dynamometers, vehicle controllers, virtual environments, and radar, camera, positioning, or other sensor-stimulation systems.
• Develop closed-loop control, system synchronization, and validation methods to ensure laboratory testing accurately represents closed-course and real-world vehicle behavior.
• Apply artificial intelligence, machine learning, computer vision, time-series modeling, and generative methods to create realistic vehicle trajectories, model perception errors, and identify safety‑critical scenarios and edge cases.
• Develop scalable vehicle and traffic simulation, experimental automation, and data‑analysis tools using Python, MATLAB/Simulink, C/C++, and platforms such as dSPACE, CARLA, and SUMO.
• Lead experimental planning and system integration activities, including equipment selection, vehicle preparation, safety considerations, and coordination with external test facilities, vendors, universities, and other research partners.
• Document research methods and software; prepare sponsor deliverables, technical reports, peer‑reviewed publications, and presentations; contribute to research proposals; and mentor students and junior researchers.
• 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. in Mechanical Engineering, Automotive Engineering, Electrical Engineering, Computer Engineering, Robotics, or a related field.
• At least one year of relevant research or professional experience in vehicle systems, connected and automated vehicles, ADAS, controls, robotics, or transportation systems. Relevant graduate research experience may be considered.
• Experience developing or using VIL, HIL, software‑in‑the‑loop, or other real‑time simulation and testing environments.
• Experience with vehicle dynamics, feedback control, vehicle communication interfaces, drive‑by‑wire systems, or related vehicle‑control technologies.
• Proficiency in Python and MATLAB/Simulink for modeling, data processing, algorithm development, or experimental control.
• Experience applying one or more artificial intelligence or data‑driven methods, such as deep learning, computer vision, time‑series analysis, generative modeling, reinforcement learning, or sensor fusion.
• Demonstrated ability to develop and integrate experimental hardware and software systems.
• Demonstrated record of technical publications, presentations, or sponsor‑facing research reports.
• Strong written and verbal communication skills and the ability to work effectively in multidisciplinary research teams.

Preferred Qualifications:

• Experience developing and validating VIL or HIL test methods for production ADAS or automated‑driving systems, including closed‑loop vehicle testing and sensor stimulation.
• Experience integrating real‑time simulation, vehicle‑control, and traffic‑simulation platforms such as dSPACE, CARLA, SUMO, or comparable tools.
• Experience applying machine learning, computer vision, time‑series analysis, generative AI, or sensor fusion to vehicle trajectories, perception modeling, edge‑case generation, or transportation safety research.
• Experience designing experiments and evaluating correlation among laboratory, closed‑course, simulation, and real‑world results.
• Experience leading multidisciplinary, sponsor‑funded research and coordinating with government agencies, universities, industry partners, vendors, or external test facilities.
• A demonstrated record of technical publications, proposal development, research partnerships, and mentoring students or junior researchers.
• A self‑directed and collaborative approach, with the ability to manage multiple priorities and adapt to evolving research needs.

Special Requirements:

• For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post‑employment background investigation.
• To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
• For foreign national candidates: If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three‑year residency requirement, you will be required to obtain a PIV credential to maintain employment.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on‑site fitness, banking, and cafeteria facilities are also available for added 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.

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.

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.