Graduate AI Intern: Transportation Safety & Operations

National Laboratory of the Rockies; Golden (CO); On-site; USD 45,000 - 71,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

403(b) retirement plan

Sick leave

Job summary

National Laboratory of the Rockies (NLR) invites graduate interns to contribute to the AI for transportation safety and operations program. The role blends research with program support, including roadmap development and portfolio planning, while performing applied AI research on traffic safety and operations.

Ideal candidates have strong Python AI experience, coursework in transportation or data science, and excellent communication skills to present complex ideas to diverse audiences.

Qualifications

• Minimum GPA 3.0.
• Undergrad: full-time enrolled; post-undergrad within 12 months.
• Graduate: full-time master's; post-master within 12 months; PhD student eligibility.

Responsibilities

• Conduct technology and literature scans of emerging AI methods and summarize relevance, maturity, and risks for FHWA.
• Develop and evaluate AI and machine-learning models for traffic operations and safety (e.g., prediction, control, anomaly detection).
• Process and integrate multimodal transportation datasets and validate findings against field data.
• Write well-documented Python code and run workflows on NLR’s HPC systems as needed.
• Document methodologies and results, and contribute to technical reports, presentations, and publications.
• Support program coordination: inventories of projects, datasets, models, and outcomes; prepare briefings and workshop materials.

Skills

Python for data analysis

AI methods

Transportation data

Communication skills

Optimization

Traffic flow theory

Game theory

Traffic operations

Education

Bachelor's program

Master's program

PhD candidate

Tools

Git

HPC systems

Job description

National Laboratory of the Rockies (NLR) invites graduate interns to contribute to the AI for transportation safety and operations program. The role blends research with program support, including roadmap development and portfolio planning, while performing applied AI research on traffic safety and operations.

Ideal candidates have strong Python AI experience, coursework in transportation or data science, and excellent communication skills to present complex ideas to diverse audiences.