[Hiring] Graduate Intern - Artificial Intelligence for Power System Operations @National Laboratory of the Rockies

Role 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.

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

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.
• 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.

Requirements

• The successful candidate will have completed an undergraduate degree and either be enrolled in or recently graduated from a master's 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 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.

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.
• 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.

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.