Graduate Fall Intern: Hybrid Energy Systems Modeling

National Renewable Energy Laboratory

Colorado

On-site

USD 45,000 - 71,000

Part time

14 days+
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Benefits offered by this job

medical, dental, and vision insurance
403(b) Employee Savings Plan with ERS
sick leave

Job summary

National Renewable Energy Laboratory is seeking a Graduate Fall Intern to design and optimize distributed hybrid energy systems. The role focuses on integration across generation, storage, distribution, and chemical end-uses, with emphasis on real-time scalable analyses using tools like H2Integrate.

Ideal candidates are pursuing advanced degrees, have Python experience, and can contribute to publishing results and presenting at conferences.

Qualifications

  • Minimum GPA 3.0 or higher.
  • Undergraduate: enrolled full-time in a bachelor’s program.
  • Post undergraduate: bachelor’s degree within past 12 months; internship up to one year.
  • Graduate: enrolled full-time in a master’s program.
  • Post graduate: master’s degree within past 12 months; internship up to one year.

Responsibilities

  • Design and run analyses and optimizations of distributed hybrid energy systems.
  • Determine optimal sizing both technically and economically.
  • Deploy scalable real-time strategies for varying plant sizes.
  • Publish results in technical journals and present at conferences.
  • Support development of new proposals and reviews.

Skills

Python programming
Distributed hybrid energy systems
Modeling chemical processes

Education

Bachelor's degree (within past 12 months)
Master's degree (within past 12 months)
PhD student (enrolled)

Tools

H2Integrate
High performance computing

Job description

National Renewable Energy Laboratory is seeking a Graduate Fall Intern to design and optimize distributed hybrid energy systems. The role focuses on integration across generation, storage, distribution, and chemical end-uses, with emphasis on real-time scalable analyses using tools like H2Integrate.

Ideal candidates are pursuing advanced degrees, have Python experience, and can contribute to publishing results and presenting at conferences.

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