Graduate (Year-Round) Intern - Transportation Systems Analysis

National Renewable Energy Laboratory • Golden, CO

2d

About The Position

Seeking full - or part-time graduate candidates to work with researchers in NLR Center for Integrated Mobility Sciences on database development, data processing, and dashboard development to support analysis of mobility trends and energy implications of emerging transportation technologies. Specific tasks may include: Assist NLR researchers on projects providing insights into transportation energy systems, with a focus on how emerging transportation systems impact travel behavior, quality of life, and energy use. Analyze large-scale real-world travel activity, vehicle driving, and geospatial datasets using scalable, high-performance computing approaches. Contribute to the development and enhancement of population evolution and demographic microsimulation frameworks, including model design, calibration, validation, and scenario analysis; clearly communicate modeling approaches and findings to technical and non-technical stakeholders. Evaluate transportation accessibility outcomes alongside economic and outcomes, and help quantify tradeoffs and co-benefits associated with emerging mobility systems, infrastructure investments, and policy interventions. Generate insights from transit datasets, including General Transit Feed Specification (GTFS), ridership, usage, and fare data to evaluate transit performance and accessibility. Deliver quality products that synthesize external literature, data analyses, and modeling results. Document methods and assumptions and assist with preparing peer-reviewed publications along with high-quality technical reports and presentations.

Requirements

• Minimum of a 3.0 cumulative grade point average.
• Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution. Post Undergraduate: Earned a bachelor’s degree 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 from an accredited institution. 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.
• Experience working with quantitative data and performing statistical or analytical tasks
• Proficiency in at least one programming or analytical tool such as Python, R, MATLAB, or SQL
• Ability to create clear and accurate data visualizations using tools such as Python (Matplotlib/Seaborn), R (ggplot2), or similar
• Experience handling large or complex datasets
• Strong problem-solving skills and attention to detail
• Good written and verbal communication skills

Nice To Haves

• Experience with demographic or population modeling or longitudinal data
• Experiences with transportation modeling, travel demand modeling, or land use and transportation interaction
• Familiarity with GIS tools
• Experience applying ML or data-driven methods to forecasting, behavioral modeling, or pattern recognition
• Familiarity with ML libraries or frameworks such as scikit-learn, TensorFlow, PyTorch, or similar
• Cumulative undergraduate/graduate GPA over 3.5 on a 4.0 scale.

Responsibilities

• Assist NLR researchers on projects providing insights into transportation energy systems, with a focus on how emerging transportation systems impact travel behavior, quality of life, and energy use.
• Analyze large-scale real-world travel activity, vehicle driving, and geospatial datasets using scalable, high-performance computing approaches.
• Contribute to the development and enhancement of population evolution and demographic microsimulation frameworks, including model design, calibration, validation, and scenario analysis; clearly communicate modeling approaches and findings to technical and non-technical stakeholders.
• Evaluate transportation accessibility outcomes alongside economic and outcomes, and help quantify tradeoffs and co-benefits associated with emerging mobility systems, infrastructure investments, and policy interventions.
• Generate insights from transit datasets, including General Transit Feed Specification (GTFS), ridership, usage, and fare data to evaluate transit performance and accessibility.
• Deliver quality products that synthesize external literature, data analyses, and modeling results.
• Document methods and assumptions and assist with preparing peer-reviewed publications along with high-quality technical reports and presentations.

Benefits

• Benefits include medical, dental, and vision insurance
• 403(b) Employee Savings Plan with employer match
• sick leave (where required by law).
• NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component.
• Some positions may be eligible for relocation expense reimbursement.

What This Job Offers

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