Graduate Fall Intern – Modeling and Analysis of Distributed Hybrid Energy Systems

Posting Title Graduate Fall Intern – Modeling and Analysis of Distributed Hybrid Energy Systems

Location CO - Boulder

Position Type Intern (Fixed Term)

Hours Per Week 40

Working at NLR

NLR’s 305-acre Flatirons Campus is the nation’s premier wind energy, water power, and grid integration research facility. Nestled south of Boulder, Colorado, and north of NLR’s main South Table Mountain campus, Flatirons Campus sits adjacent to the Rocky Flats National Wildlife Refuge and countless acres of open space and parks with stunning views of the Flatirons rock formations. 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

NLR is seeking a graduate fall intern design and optimize distributed hybrid energy systems focused on producing chemical end‑uses. This will feature integration of technologies such as across generation, storage, the distribution system, and chemical end‑uses. The intern will design and run analyses and optimizations of distributed hybrid energy systems to determine optimal sizing technically and economically. The researcher will need to deploy scalable strategies for varying hybrid plant sizes in real‑time.

The researcher will use a variety of simulation tools including, H2

Integrate. This researcher is expected to demonstrate a broad understanding and wide application of engineering principles, theories and concepts as well as general knowledge of hybrid energy related disciplines and applications. The researcher will work with a variety of customers including federal, state, and industry partners. The successful candidate will have excellent writing, interpersonal and communication skills. The candidate will be expected to help publish results in technical journals/conference proceedings and present work at conferences, symposia, and sponsor review meetings.

They will also be expected to support the development of new work proposals, preparations, and reviews.

• 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.
• Must meet educational requirements prior to employment start date.

Additional Required Qualifications

The preferred candidate will have experience with distributed hybrid energy system design and experience with modeling chemical processes such as ammonia. The preferred candidate will have experience with Python programming languages and be comfortable working in high performance computing…