National Renewable Energy Laboratory | Graduate Summer Intern – Power System Operation and Machine Learning Applications | United States | United States | BigDataKB.com | 2023-01-16

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Job Location: United States

Job Detail:

Posting Title

Graduate Summer Intern – Power System Operation and Machine Learning Applications

Location

CO – Golden

Position Type

Intern (Fixed Term)

Hours Per Week

40

COVID-19 Safety Protocols

Employment at NREL is contingent upon your compliance with all NREL and U.S. Department of Energy (DOE) safety protocols and mitigation efforts directed at the COVID-19 pandemic.

Working at NREL

The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation’s primary laboratory for research and development of renewable energy and energy efficiency technologies.

From day one at NREL, you’ll connect with coworkers driven by the same mission to save the planet. By joining an organization that values a supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our eight employee resource groups, numerous employee-driven clubs, and learning and professional development classes.

NREL supports inclusive, diverse, and unbiased hiring practices that promote creativity and innovation. By collaborating with organizations that focus on diverse talent pools, reaching out to underrepresented demographics, and providing an inclusive application and interview process, our Talent Acquisition team aims to hear all voices equally. We strive to attract a highly diverse workforce and create a culture where every employee feels welcomed and respected and they can be their authentic selves.

Our planet needs us! Learn about NREL’s critical objectives, and see how NREL is focused on saving the planet.

Note: Research suggests that potential job seekers may self-select out of opportunities if they don’t meet 100% of the job requirements. We encourage anyone who is interested in this opportunity to apply. We seek dedicated people who believe they have the skills and ambition to succeed at NREL to apply for this role.

Job Description

This position is looking for a student intern who has strong technical background in machine learning, reinforcement learning, AI applications in power systems, ideally on the distribution grid and building load applications. The intern will work on projects developing learning-based analytics, controls and optimizations for power systems and distributed energy resources (DERs).

The ideal candidate should be able to conduct research work independently and also collaborate with project PI and other researchers from the same project team. Ideal candidates should have strong machine learning and programming background, or strong background in power system operations and optimizations.

Onsite work is highly preferred for this role.

Basic Qualifications

Must be enrolled as a full-time student in a Bachelor’s, Master’s or PhD degree program, or graduated in the past 12 months from an accredited institution. Internship period cannot exceed 12 months past graduation. Minimum of a 3.0 cumulative grade point average.

Please Note

  • You will need to upload 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.

Preferred Qualifications

Additional Required Qualifications

  • Experienced in machine learning, deep learning, reinforcement learning, including fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
  • Have research background in power systems, distribution grids, building and vehicle grid integrations
  • Proficiency in using Python and machine learning/reinforcement learning packages
  • Basic knowledge of power system modeling and power system optimization
  • Basic experience in using power system simulation software (e.g. OpenDSS, GridLab-D, CYMDIST)
  • Experience in using high performance computers, Linux systems

Annual Salary Range (based on full-time 40 hours per week)

Job Profile: Graduate II / Annual Salary Range: $40,500 – $64,800

NREL takes into consideration a candidate’s education, training, and experience, as well as the position’s work location, 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

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.

EEO Policy

NREL is an Equal Opportunity/Affirmative Action 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, 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.

EEO is the Law | Pay Transparency Nondiscrimination | Reasonable Accommodations

E-Verify www.dhs.gov/E-Verify|For information about right to work, click here for English or here for Spanish.

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