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Postdoctoral Researcher - Controls, Emulation, and Scale-up for Clean Energy Transition

💼 Graduate Job


🤑 $73.2K - $120.8K

AI generated summary

  • You must be a recent PhD graduate with expertise in controls, emulation, and clean energy transition. Strong communication skills and experience working in multidisciplinary teams are essential. Preferred qualifications include knowledge of AI, machine learning, and statistical techniques.
  • You will research control algorithms for clean energy systems, develop scalable implementations, test emulation techniques, and collaborate with scientists to enhance solutions. Published work is a key focus.

Graduate Job

Research & DevelopmentGolden


  • NREL’s Hybrid Energy Systems team has an immediate opening for a full-time postdoctoral researcher for conducting research in controls, emulation, and the scaling-up of new and novel clean energy technologies with a particular emphasis on developing novel algorithms for applied energy challenges that are effective at large deployment scales.
  • The Hybrid Energy Systems group performs research to advance the research, integration, and demonstration of thermal, mechanical, wind, solar, battery and other storage technologies as well their end uses in mobility, buildings, and industrial processes, this involves real-time modeling and orchestration of 1000s of edge devices at individual, local, regional, to national scales. In this pursuit we work closely with the U.S. Department of Energy (DOE), industry partners, and academic institutions. The group’s work involves the development of modeling, simulation, emulation, control, and optimization approaches for various combinations of energy generation and end use applications.


  • Must be a recent PhD graduate within the last three years.* Must meet educational requirements prior to employment start date.
  • Additional Required Qualifications:
  • PhD in Computer Science, Computer Engineering, Computational Science, Applied Mathematics, Electrical Engineering, Mechanical Engineering or related disciplines.
  • Knowledge of real time device emulation and power & controller hardware-in-the-loop techniques
  • Deep knowledge of computing or computational approaches for modeling, simulation, and/or control of instrumented systems
  • Strong social and communication skills and experience in working with multidisciplinary teams
  • Experience in working with multidisciplinary teams
  • Preferred Qualifications:
  • Demonstrated knowledge of control approaches such as adaptive dynamic programming, learning-based methods, distributed control, and optimization
  • Knowledge of Artificial Intelligence, machine learning, deep learning, active learning, transfer learning, etc.
  • Knowledge of statistical techniques including sampling strategies and the design of experiments
  • An interest in societal aspects of the use of AI for engineering solutions
  • Strong publication records in the areas of expertise

Education requirements


Area of Responsibilities

Research & Development


  • Conducting research and development of control algorithms for interconnected, dynamic, and non-linear systems and transitioning them to robust scalable implementations for hybrid energy systems
  • Developing emulation techniques that can be vetted in experimental setups
  • Discovering and developing techniques to incorporate streaming data at the edge that are used to enhance solutions
  • Working with scientists across multiple domains to implement robust solutions
  • Maintain an active publishing profile in peer reviewed journals and top tier conferences


Work type

Full time

Work mode





73200 - 120800 USD