Graduate (Year-Round) Intern - Transportation… at National… · Golden

Summary: The National Laboratory of the Rockies (NLR) is the nation's primary laboratory for energy systems research and development. They are seeking a Graduate Intern to assist researchers in analyzing transportation energy systems and emerging technologies, focusing on data processing and dashboard development. 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 Required Qualifications: - 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 Preferred Qualifications: - 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 Required Skills: Statistical analysis, Data visualization, Python, Large dataset handling Important Skills: R, MATLAB, SQL, GIS tools Nice-to-Have Skills: Problem-solving, Attention to detail, Communication skills Benefits: Medical, dental, and vision insurance, 403(b) Employee Savings Plan with employer match, Sick leave (where required by law), Performance-, merit-, and achievement- based awards that include a monetary component, Relocation expense reimbursement