Graduate Intern – Artificial Learning and Intelligence for Transportation Safety and Operations

National Laboratory of the Rockies • Golden, CO

4d • Onsite

About The Position

The Artificial Learning and Intelligent Systems Group in the Computational Science Center at the National Laboratory of the Rockies (NLR) has two openings for graduate student researchers supporting the Federal Highway Administration (FHWA) Office of Safety and Operations Research and Development Super Intelligence (SI) Program. The program aims to improve highway safety and efficiency through research, program planning, stakeholder communication, and practical guidance for transportation agencies.

Interns will collaborate with NLR researchers and FHWA program staff on AI program support and applied AI research for traffic safety and operations. Program support includes contributing to roadmap development, portfolio planning, technology assessments, and technical communications. Research may address traffic flow prediction, speed limit control, cooperative driving automation, and detecting, predicting, and explaining traffic anomalies such as non-recurrent congestion and crashes. The role involves processing transportation data, validating findings against field data, documenting work, and communicating results to technical and non-technical audiences.

Requirements

• Minimum cumulative GPA of 3.0.
• For the graduate student pathway, be enrolled as a full-time student in a master's degree program at an accredited institution.
• Alternatively, the posting lists eligibility for graduate-level applicants who earned a master's degree within the past 12 months, or who have completed a master's degree and are enrolled as a PhD student at an accredited institution.
• Proficiency in Python for data analysis and machine learning, using tools such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
• Hands-on experience developing or applying modern AI methods, such as deep learning or large language models.
• Coursework or project experience in transportation or traffic engineering, computer science, or data science.
• Excellent written and verbal communication skills, including the ability to summarize technical work for non-technical audiences.
• Ability to work on a multi-organization team.
• Meet educational requirements before the employment start date.
• Provide official or unofficial school transcripts as part of the application process; a letter of recommendation will be required if selected.

Nice To Haves

• Experience in optimization, including quantum computing, game theory, statics, and traffic flow theory.
• Experience with traffic operations or safety data, such as detector, probe, trajectory, video, or crash data, or with Transportation Management Center operations.
• Familiarity with causal inference, anomaly detection, meta-learning, or synthetic data generation.
• Experience building applications with large language models, such as retrieval-augmented generation, agents, or automated document analysis.
• Experience supporting research programs through technology assessments, roadmaps, literature reviews, or policy and briefing documents.
• Familiarity with responsible or trustworthy AI concepts, such as AI risk management, model transparency, and data governance, in a public-sector context.
• Prior publications or presentations in transportation or computer science venues.
• Experience running code on high-performance computing systems and using Git.

Responsibilities

• Conduct technology and literature scans of emerging AI methods, such as large language models, foundation or world models, and agentic AI, and summarize their relevance, maturity, and risks for FHWA.
• Develop and evaluate AI and machine-learning models for traffic operations and safety, including traffic flow prediction, speed limit control, cooperative driving automation, and traffic anomaly detection, prediction, and explanation.
• Process and integrate multimodal, multisource transportation datasets, such as sensor, video, trajectory, and incident data, and validate findings against field data.
• Write well-documented Python code and run workflows on NLR high-performance computing systems as needed.
• Document methodologies and results, and contribute to technical reports, presentations, and publications.
• Organize and characterize the SI program's project portfolio, including inventories of projects, datasets, models, and outcomes, to inform planning and investment decisions.
• Prepare briefings, white papers, fact sheets, and presentation materials for FHWA leadership, stakeholders, and workshops.
• Support program coordination by tracking tasks and progress, preparing meeting materials, and documenting decisions and action items.

Benefits

• Medical, dental, and vision insurance, subject to eligibility rules.
• 403(b) Employee Savings Plan with employer match.
• Sick leave where required by law.
• Potential eligibility for performance-, merit-, and achievement-based awards with a monetary component.
• Some positions may be eligible for relocation expense reimbursement.
• Professional development opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern