Seeking full- or part-time graduate or highly qualified undergraduate interns to work with researchers in NREL’s Center for Integrated Mobility Sciences on data processing/analysis, development of a long-distance freight transportation demand model, and application of the model to quantify the mobility and energy implications of emerging freight transportation technologies. Specific tasks may include:
- Assist NREL researchers on projects that understand and characterize freight transportation systems to accurately simulate freight shipment and vehicle movement and quantify the impact of vehicle electrification on transportation systems and the grid.
- Process and analyze large quantities of freight shipment data and vehicle operation data.
- Work towards the development of a scalable, distributed, and data-driven long-distance freight demand model, which enables the generation of daily freight OD flows and corresponding vehicular traffic on the nation-wide network.
- Support to integrate the demand model into NREL’s Highly Integrated Vehicle Ecosystem (HIVE) Simulation Framework and to run different levels of long-haul vehicle electrification scenarios to evaluate the impact of freight electrification on grid demand for a region. Information regarding HIVE can be found at https://www.nrel.gov/transportation/hive.html.
- 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.
This internship is funded until September 2023 with possibility for extension depending on other projects available. A year-round internship is strongly preferred.
Must be enrolled as a full-time student in a Bachelor’s, Master’s or PhD degree program, or graduated in the past 12 months from an accredited institution. Internship period cannot exceed 12 months past graduation. Minimum of a 3.0 cumulative grade point average.
•You will need to upload official or unofficial school transcripts as part of the application process.
•If selected for position, a letter of recommendation will be required as part of the hiring process.
Additional Required Qualifications
Highest priority preferred qualifications:
- Strong collaboration skills—thrives working in a collaborative team environment but is comfortable working independently when necessary.
- Demonstrated programming proficiency in Python and R.
- Familiarity with data processing and analysis using computer software programs.
- Familiarity with transportation data, especially freight related data (e.g., Freight Analysis Framework and Commodity Flow Survey data).
- Knowledge in transportation demand modeling.
Additional preferred qualifications:
- Experience in transportation systems and/or computational sciences.
- Familiarity with network theory.
- Skilled in problem-solving, written, and verbal communication.
- Experience with collaborative software development and use of Git/GitHub for project management and version control.
- Cumulative undergraduate/graduate GPA over 3.5 on a 4.0 scale.
Please include all relevant experience and qualification information on the uploaded PDF (or MS Word) copy of your resume or CV.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Graduate I / Annual Salary Range: $41,600 – $66,600
NREL takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.
About The National Renewable Energy Laboratory (NREL)
The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.