NREL Postdoctoral Researcher - Computational Modeling of Combustion in Golden, Colorado

Posting Title

Postdoctoral Researcher - Computational Modeling of Combustion



CO - Golden


Position Type

Postdoc (Fixed Term)


Hours Per Week



Job Summary

Applicants are invited to apply for a postdoctoral position in the Biosciences Center to develop predictive computational models for combustion research. These models will focus on identifying bio-derived fuel candidates for next generation engines.

Job responsibilities include the following:

  • Propose detailed chemical reaction mechanisms and perform mechanism reduction techniques based on chemical intuition and pathway flux analysis.

  • Perform kinetic modeling of combustion reactions using Cantera and/or ChemKin.

  • Perform ab initio calculations using standard software packages (e.g. Gaussian) based on proposed mechanisms, and calculate rate rules for these mechanisms using RRKM theory.

  • Incorporate machine-learning methodologies for development of rapid predictive and screening tools.

  • Interact with modeling and experimental collaborators at NREL and other institutions to analyze and discuss projects.

  • Effectively communicate and interact with scientists and engineers to define the requirements of the simulations and models. Obtain necessary input data for simulations and provide meaningful interpretation of modeling results to guide experiments, operations, and engineering designs.

  • Disseminate knowledge through publications in technical journals and presentations at conferences, symposia, and review meetings. Provide reports on technical work and input to technical publications and presentations.

  • Work with management and senior staff to plan and design projects, determine technical objectives, and interact with and provide regular project reports to government and/or industrial clients.

The successful candidate will have the following skills and experiences:

  • Strong background in combustion chemistry and physics, modeling and kinetics preferably with an emphasis on bio-fuels applications.

  • Fluency in at least one scientific programming environment (Python/R/MATLAB), including techniques for data manipulation, and machine learning.

  • Comfortable with UNIX and HPC environments; experience with git workflows preferred.

  • Well-versed in quantum chemistry and related software, e.g. Gaussian.

  • Demonstrated experience in performing simulations studies that inform and collaborate with experimental projects.

  • Ability to work independently and in teams to deliver high-quality results within aggressive timelines.

  • Excellent technical writing, interpersonal, and communication skills.

  • Troubleshooting and problem-solving skills.

  • Recent (within past three years) PhD in Chemistry, Chemical Engineering, Mechanical Engineering or related field with a focus on computational modeling.

  • Dedication to a safe and clean work environment.


Required Education, Experience, and Skills

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


Preferred Qualifications

Strong publication record. Applicants should be fluent in at least one scientific programming environment (Python, R, MATLAB, Perl, etc.). A strong background in mathematics and computational statistics, DFT calculations, and chemical kinetics are essential. Experience with machine learning training/validation/testing paradigm is highly preferred. In-depth knowledge of combustion chemistry/physics is critical.


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