Posting Title
Researcher – Wind Turbine Condition Monitoring, Wind Plant Operations & Maintenance, and Wind Energy Digitalization

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Location
CO - Boulder

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Position Type
Postdoc (Fixed Term)

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Hours Per Week
40

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Working at NREL
NREL’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 NREL’s main South Table Mountain campus, Flatirons 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.

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

The National Wind Technology Center at the NREL Flatirons Campus is seeking a qualified candidate to help execute projects related to wind turbine condition monitoring, wind plant operations & maintenance, and wind energy digitalization. NREL has been conducting research in wind turbine condition monitoring, wind plant operations & maintenance (O&M), and wind energy digitalization to help improve operational reliability of turbine components and reduce O&M costs at wind plants. There is a need for a researcher with experience in condition monitoring, O&M, advanced data analytics, e.g., machine learning and artificial intelligence, to investigate fault diagnostics and prognostics techniques based on data-driven (e.g., machine learning algorithms) and physics-domain modeling approaches, O&M optimization by considering component degradation and uncertainties, and open-source software tools, etc. The candidate will apply hybrid modeling techniques for component fault prognostics to accomplish optimized O&M at wind plants including both land-based and offshore, implement on open-source digital platform and demonstrate.

The researcher will work with a wide variety of customers including the U.S. Department of Energy Wind Energy Technology Office. They may also work collaboratively with other national laboratories, industry and academic partners, and the international community to execute projects and promote the wind industry. The researcher is expected to demonstrate a broad understanding and wide application of engineering principles, theories, and concepts as well as general knowledge of wind energy-related disciplines, applications, and challenges.  Candidates with mechanical, aerospace, statistics, or data science backgrounds with some knowledge of wind engineering applications are encouraged to apply.

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Basic Qualifications
Must be a recent PhD graduate within the last three years.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

The successful candidate will have excellent writing, interpersonal, and communication skills. The candidate will be expected to publish research results in technical journals/conference proceedings and present work at conferences, symposia, and review meetings. They will also be expected to support the development of new work proposals, preparations, and reviews.

Preferred Qualifications

·       Experience with wind turbine drivetrain component fault detection, diagnostics and prognostics based on SCADA or vibration or oil data analysis.

·       Experience with physics-domain fault degradation modeling, bearing or gear life assessment. 

·       Experience with hybrid modeling combining machine learning algorithms and physics domain approaches.

·       Experience with programming languages, including familiarity with Python and/or MATLAB, machine learning packages, or high-performance computing environments.

·       Experience with standard software workflows on GitHub, including issue tracking and submitting/reviewing pull requests from development branches.

·       Experience with modern software engineering best practices, including object-oriented programming, unit and regression testing and documentation.

·       Experience with acquiring, reducing, and analyzing large experimental data sets using LabVIEW and MATLAB or other open-source software (e.g., Python).

·       Familiarity with wind turbine systems.

·       Familiarity with uncertainty quantification.

·       Knowledge of prognostics and health management framework.

·       Knowledge of gearbox and bearing design standards.

·       Wind turbine analysis experience.

·       Demonstrated ability to organize and clearly present complex concepts and results.

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Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $71,300 - $117,600

NREL takes into consideration a candidate’s education, training, and experience, 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; short-term disability insurance*; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. 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.

* Based on eligibility rules

Drug Free Workplace

NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

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

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, 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.

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