Graduate Intern - AI/ML for Mobility Research and Analysis

Posting Title Graduate (Summer or Year-Round) Intern for the Application of AI/ML for Mobility Research and Analysis . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per Week 40 . Working at NREL Join a team of world-class scientists, engineers, and visionaries dedicated to shaping the world’s energy future through cutting-edge research and innovation. From our vision to our NREL community, we are unique in the research community. We are focused on impact. From our work in basic sciences to systems engineering, analysis, demonstration, and deployment, we are focused on solving market-relevant problems that result in advanced, secure, reliable, and affordable energy systems. We are trusted clean energy leaders, developing cost-saving solutions that make U.S. industries more competitive, and support job creation and economic growth across rural and urban communities. At NREL, we offer a unique, mission-driven work environment with cutting-edge facilities and multidisciplinary research teams. NREL's environment offers strong partnerships with industry, academia, and other national laboratories, as well as professional development opportunities and a competitive benefits package for employees. Learn about NREL’s critical objectives: NREL's Mission and Vision. Job Description Seeking part-time or full-time graduate intern to work with researchers in NREL’s Center for Integrated Mobility Sciences, Mobility Innovation and Efficiency (MIE) Team to apply advanced data processing, in the form of Machine Learning and Artificial Intelligence to the analysis and research of new mobility. Specific tasks may include: Develop a sentiment analysis tool using data harvested from social media on the attitudes and user benefits and issues associated with rapidly scaling vehicle automation such as Waymo Robo-taxis and other automated public mobility initiatives. In addition, utilize LLaMA or Claude-like large language models to infer user behavior from users’ social media comments or posts. Research use of AI/ML to augment or supplant traditional stochastic and Bayesian methods for multi-track sensor fusion, and compare and contrast it with more algorithmic approach using Bayesian association and Kalman filtering, particularly with respect to object permanence through the field of observation. Assist NREL researchers on applications of ML/AI in various fields of transportation infrastructure and vehicle engineering, with particular emphasis on DOT functions and responsibilities. Experiment with large language models and their associated tools to increase the productivity of research within the MIE team including literature review, drafting of initial results, and refinement of final product. Document methods and assumptions and assist with preparing peer-reviewed publications along with high-quality technical reports and presentations. . Basic 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. Please Note: • Applicants are responsible for uploading 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. • Must meet educational requirements prior to employment start date. * Must meet educational requirements prior to employment start date. Additional Required Qualifications Experience across a large variety of current AI/ML tools. Fundamental knowledge of transportation engineering/planning, ideally including expertise in current mobility standards and practices as they pertain to automated mobility and traffic engineering. Preferred Qualifications Highest priority preferred qualifications: Educational and experience background in Computer Science and Civil Engineering – Masters degree or above in both. Experience—either employment, project, or internship—with a Department of Transportation of significant length to understand the structure and responsibilities of a DOT. Strong collaboration skills—thrives working in a collaborative team environment but is comfortable working independently when necessary. Ability to organize research results using meaningful and insightful methods. Additional preferred qualifications: Experience working with large datasets. Experience in transportation infrastructure. Experience in traffic engineering. Strong writing and presentation skills. 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. Ideally, please also add a link to your GitHub (or GitLab, etc.) profile and ensure that as many repos as possible are public. . Job Application Submission Window The anticipated closing window for application submission is up to 30 days and may be extended as needed. Annual Salary Range (based on full-time 40 hours per week) Job Profile: / Annual Salary Range: $43,700 - $69,900 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. Benefits Summary Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NREL 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. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits. * Based on eligibility rules Badging Requirement NREL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement. Drug Free Workplace NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug. If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn. Submission Guidelines Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application. . 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With locations in Golden and Boulder, Colorado, and a satellite office in Washington, D.C., NREL is the primary laboratory for research, development, and deployment of renewable energy technologies in the United States. NREL is subject to Department of Energy (DOE) access restrictions. All candidates must be authorized to access the facility per DOE rules and guidance within a reasonable time frame for the specified position in order to be considered for an interview and for hiring. DOE rules for site access during the interview process depend on whether the candidate is interviewed on-site, off-site, or via telephone or videoconference. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. 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