3-5 years of experience
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Employment Type:
Full time
Job Category:
Postdoctoral Researcher - Scalable Infrastructure Planning
(This job is no longer available)
Grad Date

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Job Description

The Complex Systems Simulation and Optimization Group in the NREL Computational Science Center has an opening for a full-time postdoctoral researcher in scalable infrastructure modeling and planning via scalable optimization algorithms (SO), uncertainty quantification (UQ) and artificial intelligence (AI) to enable a highly interdisciplinary and collaborative team in developing and applying state-of-the art infrastructure system modeling to conduct leading-edge analyses. Emphasis is placed on the collaborating with a small team on the construction and solution of multi-sector infrastructure models at scale using high performance computing systems.

The successful candidate will collaborate to develop, adapt, improve, and scale cutting edge SO, UQ, and AI methods to a new class of multi-sector infrastructure models to explore emerging challenges in technology innovation, system evolution, and operation in support of NREL and EERE mission and goals. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in the mission of NREL.

Responsibilities include:

  • Collaborate with NREL researchers to design, implement and carry out numerical and computational experiments for multi-sector infrastructure modeling that are dependent on the construction and solution of SO, UQ and AI algorithms, including the implementation, and execution of workflows on HPC systems.
  • Contribute to the design and development of software architectures for the scalable execution and analysis of multi-sector infrastructure modeling.
  • Conduct independent and collaborative research in developing and using advanced SO, UQ and AI algorithms for energy systems research.
  • Evaluate and track state of the SO, UQ and AI algorithms and implementations and their use on advanced and emerging computing architectures.
  • Author, present and assist in the preparation of technical papers, reports and conference proceedings on topics related to SO, UQ and AI algorithms and their use on High Performance Computers computers.


Required Education, Experience, and Skills

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


Preferred Qualifications

  • A strong background in scalable algorithm development and implementation for scientific, engineering and analysis applications. Strong analytical skills and programming experience. Demonstrated expertise in SO, UQ and AI algorithms.
  • Demonstrated expert skill at developing parallel programs using shared memory and distributed memory mechanisms such as MPI, OpenMP, Pthreads, and CUDA.
  • Experience with optimization, solver algorithms and behavior, uncertainty quantification, and/or artificial intelligence, with applications to electrical power flow or infrastructure expansion and operation.
  • Expertise in Markov Decision Processes, deep learning (neural networks, including knowledge of core mathematical underpinnings), reinforcement learning (esp., for continuous and/or large state-action spaces).
  • Expertise in related AI concepts, including, but not limited to: Monte Carlo Tree Search, policy gradients, actor-critic methods, model-based acceleration, generative adversarial networks, trust region policy optimization, guided policy search.


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.

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.