The Civil Engineering Department seeks a Research Associate to assist with the research of prototype traffic detection devices for advanced vehicle identification and classification. This project funding this position is for commercialization and product development. The work has the strong potential to continue into highly competitive SBIR/STTR and/or NSF PFI projects for which the Research Associate could levy the product development into a small business and serve as the PI for such funding opportunities.. This position will report to Dr. Sarah Hernandez.
This position will utilize fundamental concepts, practices, and procedures to assist in the execution of research programs in the area of traffic sensor/detector design for Intelligent Transportation System (ITS) and highway traffic monitoring applications within the department of Civil Engineering. Specific job responsibilities will include:
(1) the research, design, development, specification, fabrication, testing, and debugging of prototype traffic data collection device utilizing emerging “off the shelf” non-intrusive technologies such as LiDAR and vision based devices;
(2) the development of algorithms and machine learning models for advanced vehicle identification and classification using data from the prototype sensors;
(3) the design and execution of experimental procedures in a research laboratory setting;
(4) the collection, post-processing, and analysis of data from experimental testing in field applications;
(5) the generation of technical reports and scholarly publications; and
(6) the direction and guidance of graduate research assistants in the performance of their research duties.
This position may be involved in multiple research projects; any of which may include conducting experiments, analyzing data, and assisting with writing research proposals, technical papers and research reports. The successful applicant must be willing and able to take advantage of educational and training opportunities to remain proficient and up to date with the state-of-the-art technology to support leading edge research.
Regular, reliable, and non-disruptive attendance is an essential job duty, as is the ability to create and maintain collegial, harmonious working relationships with others.
Advanced degree in a relevant engineering discipline
Hands-on experience with computer vision and/or camera hardware development and machine learning model development
Familiarity with Linux operating systems and Robot Operating System 2 (ROS2)
Knowledge, Skills and Abilities:
This position will require excellent electronics and mechanical skills
Proficiency in programming in Python, C++, or other languages
The ability to work collaboratively with faculty, staff, and students
The ability to work independently with limited supervision
* This position will be expected to supervise experiments in the laboratories and in the field, train students in the use of equipment, and to design, construct, and operate experimental hardware.
This position is renewable annually based on continued need for the position, availability of funding, and satisfactory job performance.
College of Engineering – Diversity & Inclusion Statement
The College of Engineering is dedicated to building and supporting an inclusive culture with a diverse and pluralistic faculty, staff, and administration. The College encourages applications from all qualified candidates, especially individuals who contribute to diversity of our campus community and welcomes applications without regard to race/color, sex, gender, pregnancy, age, national origin, disability, religion, marital status, protected veteran or military status, genetic information, LGBTQIA+, or any other characteristic protected under applicable federal or state law. The College invites applicants with career interruptions to share the related circumstances and explain how these interruptions have impacted their career path.
Commensurate with education and experience
Required Documents to Apply:
Cover Letter/Letter of Application, Letters of Recommendation, Resume
Proof of Veteran Status
Recruitment Contact Information:
Sandy Thomas, Assistant to Department Head, firstname.lastname@example.org
All application materials must be uploaded to the University of Arkansas System Career Site https://uasys.wd5.myworkdayjobs.com/UASYS
Please do not send to listed recruitment contact.
Pre-employment Screening Requirements:
Criminal Background Check, Sex Offender Registry
The University of Arkansas is committed to providing a safe campus community. We conduct background checks for applicants being considered for employment. Background checks include a criminal background check and a sex offender registry check. For certain positions, there may also be a financial (credit) background check, a Motor Vehicle Registry (MVR) check, and/or drug screening. Required checks are identified in the position listing. A criminal conviction or arrest pending adjudication or adverse financial history information alone shall not disqualify an applicant in the absence of a relationship to the requirements of the position. Background check information will be used in a confidential, non-discriminatory manner consistent with state and federal law.
The University of Arkansas seeks to attract, develop and retain high quality faculty, staff and administrators that consistently display practices and behaviors to advance a culture and climate that embeds inclusion, diversity, equity, and access. For more information on diversity and inclusion on campus, please visit: Division of Diversity, Equity, and Inclusion