3-5 years of experience
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Employment Type:
Full time
Job Category:
Postdoctoral Researcher – Complex Systems Integration
(This job is no longer available)
Grad Date

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Job Description

The Residential Buildings Research Group is seeking a Postdoctoral Researcher with experience in modeling and simulating complex systems. The ideal candidate will leverage their scientific mindset and a creative “get it done” mentality to address important data-driven problems related to the interactions of multiple systems – such as power systems, thermal systems, data/network systems, human and transportation systems – to enable novel approaches to design and operate smart buildings, communities, districts and cities.

Job duties and responsibilities may include:

  • Developing and implementing novel optimization methods for complex, nonlinear and dynamic systems.
  • Developing mathematical and software approaches to enable interoperation of multiple domain-specific simulation software tools, methods or models (co-simulation).
  • Applying these powerful cross-domain analytical tools to evaluate multi-technology interactions at relevant timescales.
  • Developing, implementing and evaluating strategies for advanced control, commitment and value transfer across scales, such as distributed hierarchical control, probabilistic optimization strategies, and blockchain-based transactive energy.
  • Collaborating with other NRELians to interoperate the cross-domain analysis tools with laboratory and/or field hardware, for example Hardware-in-the-Loop or Controller-in-the-Loop.
  • Writing papers for peer-reviewed science journals.


  • Effective communication skills are required.
  • Strong background in electrical engineering, power systems, applied mathematics, statistics, machine learning, optimization or related fields is required.
  • Demonstrated expertise in programming languages such as Python, R, SQL, Matlab, C++ or similar is required.
  • Proven track record of high-quality publications in peer-reviewed journals and conferences is required.
  • Demonstrated experience with relevant domain simulation tools is a major plus. Examples include building energy simulation tools such as EnergyPlus, distribution feeder simulation tools such as OpenDSS, SynerGEE or GridLAB-D, and solar simulation tools such as SAM.
  • Working knowledge of data visualization tools and version control software is a major plus.
  • Demonstrated implementation of optimization solvers, such as CVX or Gurobi, is a plus.
  • Working experience in a relevant domain – utility power systems, buildings, solar or Internet of Things (IoT) – is a plus.
  • Experience with data synthesis or big data methods and tools is a plus.
  • Experience using high-performance, cloud, or parallelized computing platforms to solve technical problems is a plus.
  • Experience with software containers and orchestration engines, such as Docker, ECS, and Kubernetes, is a plus.


Required Education, Experience, and Skills

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


Preferred Qualifications


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 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.

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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.