Experience:
Not specified
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Employment Type:
Full time
Posted:
12/5/2018
Job Category:
IT / MIS
Industry:
Government
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Postdoctoral Researcher - Distributed Generation Data Scientist
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Job Description

Distributed technologies like solar photovoltaics, storage, and wind are changing the energy landscape. This position will join our distributed generation (dGen) modeling team as we strive to understand what drives consumers to place solar panels on their roof and batteries in their basements. NREL’s dGen model modeling tool is an agent-based model that relies on rich socio-economic and geospatial data to forecast the adoption and deployment of distributed technologies like solar PV. The dGen team is looking for a research analyst with a passion for big data, economics, consumer behavior, and rate design to join their growing team. Because this is an emerging research area, we are interested in applicants from a broad background. Experience in computational science, distribution system planning, econometrics, public policy, and geographical information systems are a major plus. This position will require the successful candidate to participate in the development and execution of models, analysis of results, and publication of results in written reports and spoken presentations. Previous experience with technologies such as demand response, wind energy, solar energy, concentrating solar energy, distributed generation, and energy storage, as well as systems integration issues is a major plus. Qualified candidates must have previously published in at least one peer reviewed Journal.

Successful candidates will have qualifications in all of the following categories:

  • Demonstrated experience solving numerical scientific or engineering problems in a repeatable and/or extensible manner using programming languages such as or similar to Python, Matlab, R, C++, or Julia
  • Exposure to concepts and methods in electricity markets, power systems modeling, or other relevant engineering systems modeling
  • Experience developing statistical and/or machine-learning based models
  • Exceptional written and spoken communication skills

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Required Education, Experience, and Skills

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

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Preferred Qualifications

Preferred candidates with have qualifications in any of the following categories:

  • Prior work or academic experience on topics relating to customer adoption or customer operation of distributed energy resources
  • Prior work or academic experience on topics relating to behavioral, economic, and regulatory aspects of distributed energy resources
  • Knowledge or experience with agent-based models
  • Knowledge or experience with power systems modeling tools such as GridLAB-D or OpenDSS

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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

NREL is dedicated to the principles of equal employment opportunity. NREL promotes a work environment that does not discriminate against workers or job applicants and prohibits unlawful discrimination on the basis of race, color, religion, sex, national origin, disability, age, marital status, ancestry, actual or perceived sexual orientation, or veteran status, including special disabled veterans.

NREL validates right to work using E-Verify. NREL will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee’s Form I-9 to confirm work authorization. For additional information, click here.

About National Renewable Energy Laboratory

At NREL, we focus on creative answers to today's energy challenges. From breakthroughs in fundamental science to new clean technologies to integrated energy systems that power our lives, NREL researchers are transforming the way the nation and the world use energy.