Graduate AI Research Intern: Traffic Safety & Ops

NLR

Golden (CO)

On-site

USD 45,000 - 71,000

Part time

6 days ago

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Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

403(b) plan

Paid leave

Job summary

National Laboratory of the Rockies (NLR) seeks graduate interns to support FHWA SI program, focusing on AI for transportation safety and operations. You will engage in roadmap development, portfolio planning, and translating research into practical guidance for agencies.

The role emphasizes strong AI and Python skills, collaboration across teams, and clear technical communication to both technical and non-technical audiences. This fixed-term internship offers mentorship and project exposure.

Qualifications

Minimum of a 3.0 cumulative GPA.
Undergraduate: must be enrolled as a full-time student in a bachelor’s degree program.
Post Undergraduate: bachelor’s degree earned within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full-time student in a master’s degree program.
Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.

Responsibilities

Conduct technology and literature scans of emerging AI methods (e.g., large language models, foundation/world models, agentic AI) and summarizing their relevance, maturity, and risks for FHWA.
Develop and evaluate AI and machine-learning models for traffic operations and safety (e.g., traffic flow prediction, speed limit control, cooperative driving automation, detecting, predicting and explaining traffic anomalies such as non-recurrent congestion, and crashes).
Process and integrate multimodal, multisource transportation datasets from disparate sources (e.g., sensor, video, trajectory, and incident data) and validate findings against field data.
Write well-documented Python code and run workflows on NLR’s high-performance computing systems as needed.
Document methodologies and results, and contribute to technical reports, presentations, and publications.
Support the HRSO R&D SI program beyond research, including: organizing and characterizing the SI program’s project portfolio, preparing briefings, white papers, fact sheets, and presentation materials for FHWA leadership, stakeholders, and workshops, and supporting program coordination.