University of Texas at Arlington
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Postdoctoral Research Associate in Transportation Health, Safety, and Human Behavior University of Texas at Arlington in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time postdoctoral research associate; grant-funded appointment. Renewal, if offered, depends on satisfactory performance, continued funding, and university policy. Benefits are provided, including health insurance, retirement plans, and paid time off.
Country
United States
University
University of Texas at Arlington
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About this position
The University of Texas at Arlington is recruiting a Postdoctoral Research Associate in the Department of Civil Engineering for research in transportation health, safety, and human behavior.
The position is based in the Sustainable Mobility and Resilient Transportation (SMART) Research Lab and is supervised by Dr. Kate Hyun. The research program focuses on how individual-level decisions and behaviors influence transportation safety and health, with a strong emphasis on driving behavior, attention, risk assessment, learning, behavior change, and emerging technologies.
Core work includes designing and implementing studies with human participants, collecting sensor, simulator, and field data, analyzing repeated-measures and multimodal behavioral data, developing behavior-informed simulations using digital twins, and evaluating education, technology, and infrastructure countermeasures. The role also involves project coordination, community engagement, scholarly communication, proposal development, and student mentoring.
Relevant study areas and methods include civil engineering, transportation safety, human behavior, behavioral analysis, machine learning, deep learning, computer vision, statistics, and mixed-methods research.
Eligibility highlights: a completed Ph.D. by the start date in civil engineering (transportation-focused) or a closely related field; experience with human-participant research; strong analytical and communication skills; and experience working with agencies, community partners, or other external stakeholders. Preferred experience includes IRB processes, participant recruitment, privacy/confidentiality, and community-engaged research.
Funding: this is a grant-funded full-time postdoctoral appointment with benefits. Renewal depends on performance, continued funding, and university policy.
Application: apply via the UTA PeopleAdmin portal with a CV, cover letter, one representative writing sample, and three references. Applications are reviewed on a rolling basis and candidates are encouraged to apply early.
Location: Arlington, Texas, United States.
Funding details
Full-time postdoctoral research associate; grant-funded appointment. Renewal, if offered, depends on satisfactory performance, continued funding, and university policy. Benefits are provided, including health insurance, retirement plans, and paid time off.
What's required
Ph.D. completed by the start date in civil engineering (transportation focused) or a closely related field with research relevant to transportation health, safety, or human behavior. Applicants should have experience designing or conducting empirical research with human participants, technical capability in advanced behavioral or transportation data analysis, and experience in at least one of sensor-based data collection, driving or traffic simulation, behavior-informed digital twins, machine learning/deep learning, or computer vision. Strong written, oral, visual, and interpersonal communication skills are required, along with experience working with public agencies, community organizations, practitioners, research participants, or other external partners. Evidence of scholarly productivity and willingness to travel domestically are also required. Preferred experience includes IRB review, participant recruitment and informed consent, privacy/confidentiality, sensitive data handling, community-engaged research, and proposal development.
How to apply
Apply through the UTA PeopleAdmin portal and submit a CV, cover letter, one representative writing sample, and contact information for three references. Optional links to a code repository, technical portfolio, data visualization, or decision-support tool may also be included. Questions may be directed to Dr. Kate Hyun by email.
More information can be found here
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