Research Associate

Job Description

Transportation is undergoing an incredible transformation that is inspiring researchers to approach problems using new technologies and non-traditional methods. At the Virginia Tech Transportation Institute (VTTI), a world-leading research enterprise, we are working with government agencies, transportation and safety organizations, vehicle manufacturers and their suppliers, and others to overcome these challenges and improve transportation safety and performance on the world’s roads. (https://www.youtube.com/watch?v=Nj4VWviw5JA).

The Division of Data & Analytics (DDA) specializes in collaboration with industry, academic, and government partners to translate large-scale data collections into robust and timely guidance and decisions. The division focuses on challenging questions at the intersection of mechanical engineering, physics, computer science, statistics, behavior, performance, safety and policy. DDA projects leverage innovative data fusion approaches, algorithmic labeling processes, and interactive visualizations to translate disparate and highly dimensional data into visible progress and understandable results. The division's goals are to provide domain expertise and state-of-the-art data and analytic methods to enable our partners to answer their questions quickly, cost effectively, and with accessible output that is ready to address their most pressing needs.

VTTI seeks a qualified engineer/scientist with a strong background and proven research record in big data analysis focused on development and evaluation of vehicle systems and infrastructure elements. The ideal candidate is an experienced researcher with a desire to eventually take a leadership role in a growing and diverse research portfolio. The candidate must be capable of working collaboratively in multidisciplinary teams to complete transportation research projects within constraints of time and budget. The research projects mostly include development of advanced algorithms for data mining and modelling of human behavior and vehicle system performance.

The candidate will join the Applied Analytics Group in DDA. The focus of the team is to process large scale multimodal data to answer questions about vehicle system performance and human driving behavior. The usual research projects in this group require an understanding of large-scale naturalistic driving studies, vehicle dynamics, Advanced Driver Assistance Systems (ADAS) such as Lane Keep Assist and Adaptive Cruise Control, Automated Driving Systems (ADS), US roadway system, and other vehicle transportation related concepts. Therefore, the candidate must demonstrate previous experience related to these projects.

The candidate must be motivated to work with problems related to transportation, safety, and operation using multi modal data. The candidate must also be proficient in algorithm development, software management, and deployment using image, videos, and time series data that are applicable to safety technology and automation. The candidate must have experience in digital maps and code parallelization to run on unix based computational clusters.

RESEARCH ASSOCIATE RANK – Research Associates will be expected to carry out the following duties and responsibilities:
• Literature reviews
• Big Data Processing
• Develop and manage software
• Interpret results and develop robust conclusions
• Write research reports
• Present research findings
• Assist in the development of proposals
• Assist with the conceptualization and creation of work plans, protocols, and procedures
• Coordinate and collaborate with subcontractors and interface with stakeholders and sponsors as required
• Must be able to work effectively independently with oversight as well as within multidisciplinary project teams as appropriate

All candidates must be able to work on-site/ in office at Blacksburg Campus for majority of the work hours (at least 4 days a week). Position may sporadically involve data collection including driving and operating test vehicles.  

VTTI provides opportunities for professional advancement and a pay for performance compensation structure. The salary is commensurate with experience.

The selected candidate will require a criminal background check and valid driver's license and good driving record. Potential Travel associated with this position, up to 25% of time.

Required Qualifications

• Masters (M.S.) in engineering or related field. Candidates with a lesser degree and significant experience in the key responsibilities noted above may be considered.
• Extensive experience with processing large-scale datasets related to transportation such as naturalistic driving studies
• Experience in ADAS related vehicle systems such as LKAS and ACC
• Experience in naturalistic driving study data analysis
• Extensive experience in developing algorithms for data mining and behavior characterization.
• Expertise in Matlab, R, Python, and SQL
• Expertise in big data analysis and high-performance computing
• Expertise in digital maps such as OpenStreetMap, Here, Tomtom
• Peer reviewed publication in related field.
• Must have strong communication skills and organizational skills.
• Willingness to work in a fast paced, flexible research environment to solve complex problems and develop solutions that will improve safety on our nation’s roadways.
• Valid Driver's license

Preferred Qualifications

• Expertise in interactive visualization libraries such as Shiny
• Expertise in naturalistic driving study data analysis
• Expertise in statistical modeling and analysis
• Expertise in infrastructure and ODD related datasets
• Strong publication background in peer-reviewed journals and conferences

Appointment Type

Restricted

Salary Information

Starting rate of $70,000, commensurate with experience

Review Date

12/5/2024

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance.  These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Natalie Jett at njett@vtti.vt.edu during regular business hours at least 10 business days prior to the event.