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Research Assistant Professor - Traffic Safety

University of Tennessee - Oak Ridge Innovation Institute
Chattanooga, Tennessee
Salary determined by experience, includes benefits and start-up funding
Closing date
Dec 28, 2023

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Transportation Engineering
Position Type
Researcher / Scientist
Organization Type

Location: Chattanooga, TN – Regular collaborations and visits to the Oak Ridge National Laboratory  

Roles and Responsibilities  

UT-Oak Ridge Innovation Institute (UT-ORII) research faculty will work in collaboration with the University of Tennessee at Chattanooga (UTC) and Oak Ridge National Laboratory (ORNL) researchers to address current and future challenges of nexus of energy, transportation, and people.  Research faculty will collaborate on existing research projects and reporting, proposal preparation and submission, and student mentoring at the graduate and undergraduate levels. These positions have competitive startup packages including PhD students and budget for equipment.  

More About UT-ORII  

The University of Tennessee-Oak Ridge Innovation Institute was launched by the University of Tennessee and Oak Ridge National Laboratory in 2021, in response to  America’s need for a stronger pool of science, technology, engineering and mathematics (STEM) talent.

UT-ORII is leveraging UT and ORNL’s best capabilities and resources to accelerate collaborative discovery, innovation and interdisciplinary graduate education; and to prepare the next generation of talent in areas of critical importance to the nation and the State of Tennessee. The institute’s current convergent research areas include clean manufacturing and advanced materials, and energy storage and transportation. To learn more about UT-ORII visit

Facilities at the University of Tennessee at Chattanooga  

UTC, one of four public universities of the UT system, is recognized as a leader in experiential learning with an enrollment of approximately 11,000 students. The University is an integral part of the widely recognized educational, R&D, entrepreneurial, and economic development ecosystem of the Chattanooga Metropolitan Area (CMA), in the middle of the Tennessee Valley Science and Technology Corridor. With the support from the University of Tennessee System and close collaboration with the City of Chattanooga, UTC has established Smart Corridor , a large real-world R&D facility in downtown Chattanooga. Smart Corridor is an end-to-end platform for city-scale research, development, and validation of intelligent transportation systems, internet-of-things, edge-based AI, and connected/autonomous vehicle applications. The original testbed was deployed in 2019 consisting of a single corridor spanning 1.25 miles of urban roadway in downtown Chattanooga. Since then, the effort has grown to include the entirety of downtown Chattanooga spanning over 100 signalized intersections. Each intersection is outfitted with edge computing, communications, roadside units, cameras (thermal and RGB), audio, lidar and air quality sensors. The use of the testbed (physical and digital) is provided by our Testbed-As-A-Service (TaaS) platform. The TaaS platform provides real-time and historical data access, experiment submission, and physical asset deployment options. Currently partnering with 30 universities/ research labs/ industry at national and international levels. Several safety related projects are being executed on this facility.  

Research Faculty Position in Traffic Safety  

In alignment with State and Federal vision towards zero fatalities and serious injuries on the roadways, we seek to fill Research Faculty positions in roadway safety by the spring 2024. This position will work in close collaboartion with Dr. Mina Sartipi and will work day-in and day-out with talented data science, computer science, civil engineer, social science, and other professionals at UTC, UTK, and ORNL.  

The successful candidate will have strong knowledge and hands-on experience handling big data and building artificial intelligence models, developing and using traffic simulation and digital twins, roadway safety, an ability to collaborate with other researchers and advise graduate students, and experience with writing funding proposals.

Key Responsibilities: 
The selected candidate will:

  • Lead research studies to gather and interpret safety data specific to smart mobility infrastructure, such as IoT devices, sensors, and Connected & Autonomous Vehicles, assessing their impact on road safety.  
  • Examine driver behavior to understand the unique challenges and opportunities presented by the Smart City testbed.  
  • Engage in predictive modeling to forecast safety trends and issues, enabling proactive measures to advise on infrastructure upgrades.  
  • Guide research focusing on the safety of pedestrians, cyclists, and other vulnerable road users by identifying potential weak points or vulnerabilities.  
  • Present findings to broad audiences, proposing data-informed approach to safety enhancements.
  • Advise PhD students. 


  • PhD in Civil Engineering, Computer Science, or a related field
  • Strong knowledge and hands-on experience handling big data and building artificial intelligence models, developing and using traffic simulation and digital twins, roadway safety.
  • Strong communication skills and a ability to collaborate with other researches and advise graduate students. 
  • Track record in publications 

Preferred Qualification:

  • Track record in developing strong proposals and securing funding 
  • A clear path to independence as a researcher is desired though an ‘on-ramp’ through collaboration with more senior investigators is also encouraged. 

The position will be implemented via a 3-year, renewable contract. Salary and title/rank will be determined commensurate with experience. Benefits will be typical of exempt employees at the University of Tennessee. Some startup funds are available, and a recurring budget is also available.

Application Instructions
Review of applications will begin immediately and will continue until the position is filled. All application materials must be submitted in Interfolio at

Applications must include:

  • a letter of interest;
  • a comprehensive curriculum vitae;
  • a research plan;
  • the names, addresses, and telephone numbers of at least three professional references.

Equal Employment Opportunity Statement
All qualified applicants will receive equal consideration for employment and admission without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, genetic information, veteran status, and parental status, or any other characteristic protected by federal or state law. In accordance with the requirements of Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and the Americans with Disabilities Act of 1990, the University of Tennessee affirmatively states that it does not discriminate on the basis of race, sex, or disability in its education programs and activities, and this policy extends to employment by the university. Requests for accommodations of a disability should be directed to the Office of Equity & Diversity, 1840 Melrose Avenue Knoxville, Tennessee 37996-3560 or or (865)974-2498. Inquiries and charges of violation of Title VI (race, color and national origin), Title IX (sex), Section 504 (disability), the ADA (disability), the Age Discrimination in Employment Act (age), sexual orientation, or veteran status should be directed to the Office of Investigation & Resolution 216 Business Incubator Building 2450 E.J. Chapman Drive Knoxville, Tennessee 37996 or (865)974-0717 or

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