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NREL Internship Deep-learning techniques to identify underperformance in wind farms in Golden, Colorado

Posting Title

Internship Deep-learning techniques to identify underperformance in wind farms

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Location

CO - Golden

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Position Type

Intern (Fixed Term)

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Hours Per Week

40

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Job Description

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. There is an immediate opening in the Computational Science Center for an internship in developing novel analysis and data-reduction techniques combining deep learning techniques with high-fidelity simulations for eventual deployment to edge computing software. The intern will work in a large multi-disciplinary team to develop advanced and data-efficient fault detection techniques that can be deployed in wind farms to identify malfunctioning or underperforming turbines.

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Basic Qualifications

Must be enrolled as a full-time student in a degree granting 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 unofficial transcripts and a letter of recommendation as part of the application process.

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Additional Qualifications

The intern will work with senior NREL researchers in exploring the use of deep learning techniques combined with high-fidelity computational fluid dynamics (CFD) simulations to develop new algorithms that combines various sensor inputs (e.g., turbine performance metrics, wind inflow conditions including turbulence and stability, and other available operational data usually logged via SCADA streams) to identify malfunctioning sensors or underperforming turbines. Algorithms developed could be used to detect faulty anemometers, pitch and/or yaw misalignment, incorrect control settings, and other potential issues. Additionally, the candidate will explore the use of machine learning techniques in the field to reduce the volume of data that needs to be logged by wind plant operators without sacrificing the fidelity of the data sets for future analysis and inspection. The intern will also work with the team to prepare the results for presentation at appropriate conferences and publication in scientific journals.

Preferred Qualifications

  • Expertise in high-performance computing of fluid problems

  • Experience with deep learning techniques

  • Established publication record in peer-reviewed journals

  • Experience in computational fluid dynamics (CFD) on next-generation platforms

  • Experience with deep learning techniques combined with turbulent CFD flows

  • Experience modeling atmospheric boundary layer flows and/or wind farm flows

  • Experience with hybrid parallel-programming models

  • Expertise in modern software engineering methods

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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.

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EEO Policy

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The National Renewable Energy Laboratory (NREL) is a leader in the U.S. Department of Energy’s effort to secure an environmentally and economically sustainable energy future. With locations in Golden and Boulder, Colorado, and a satellite office in Washington, D.C., NREL is the primary laboratory for research, development, and deployment of renewable energy technologies in the United States.

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