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Graduate (3-12 month) Intern - Artificial Intelligence for Power System Operations

National Laboratory of the Rockies
Golden, CO

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Job Details

Full-time
$51,200 - $81,900 a year

Benefits

403(b) matching
Health insurance
Dental insurance
Vision insurance
403(b)

Qualifications

AI models
Programming languages
Machine intelligence
AI implementation
Neural networks
Machine learning (ML) fundamentals

Full Job Description

Posting Title

Graduate (3-12 month) Intern - Artificial Intelligence for Power System Operations

Location

CO - Golden

Position Type

Intern (Fixed Term)

Hours Per Week

Working at NLR

NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.

Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.

At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.

Job Description

This Grid Automation and Controls group at The National Laboratory of the Rockies (NLR) focuses on conducting high-impact projects to enhance power system modernization. We develop cutting edge solutions and work closely with industry and utility partners to enhance grid reliability, resilience, and security. Our team is looking for an intern who has strong technical background in machine learning (ML) and artificial intelligence (AI), ideally on large language models, natural language processing, and/or foundation models. This is a 3-month internship opportunity with the potential to extend to 12- months. This internship can be done remotely or onsite.

Job responsibilities will include but are not limited to:

Collaborating with internal and external stakeholders to advance research projects
Developing innovative AI/LLM solutions to addressing emerging power system needs
Contributing and/or leading the writing of research papers
The ideal candidate should be able to conduct research work independently

To learn more about the work this group does, check out the following link: https://www.nlr.gov/grid/distributed-energy-resource-management-systems

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

The successful candidate will have completed an undergraduate degree and either be enrolled in or recently graduated from a masters degree in computer science, data science, electrical engineering, or related fields, or be enrolled in a PhD program in these fields
Experienced in one of the following: natural language learning, large language models, foundation models, transformer models
Have a good fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
Strong in Python programming and other comparable programming languages
Self-motivated and be passionate to learn new things

Preferred Qualifications

Experience with other ML/AI techniques, including reinforcement learning and graph neural networks
Experience in using high performance computers, Linux systems
Experience in JavaScript, SQL, MongoDB, and developing interactive web-based dashboard and tools.
Familiar with power systems and know the basics of power flow

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: $51,200 - $81,900

NLR 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). 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. 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

NLR 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

NLR 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 NLR, 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 NLR 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.

Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

Reasonable Accommodations

E -Verify www.dhs.gov/E-Verify For information about right to work

E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.

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