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Postdoctoral Researcher: Computational Modeling of Combustion

Applicants are invited to apply for a postdoctoral position in the Biosciences Center to develop predictive models and statistical correlations for advanced biofuels research. The applicant will work closely with both experimental and computational researchers to extend fuel property prediction models to biofuel mixtures and develop correlative models for particulate matter formation in diesel engines, with the goal of guiding future fuel selection and optimizing performance in conventional and future compression ignition engines.
Job responsibilities include the following:
  • Propose detailed chemical reaction mechanisms and perform mechanism reduction techniques based on chemical intuition and path flux analysis.
  • Perform kinetic modeling of combustion reactions using RRKM and ChemKin/Cantera.
  • Perform ab initio calculations using standard software packages (e.g. Gaussian) based on mechanisms that you developed.
  • Create improved models based on group contribution or machine learning and/or numerical simulation approaches
  • Develop statistical methodology for predicting particulate matter emissions as a function of fuel composition and fuel properties for diesel combustion.
  • 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.

Requirements:

Must be a Ph. D. graduate within the last three years in Chemical Engineering, Mechanical Engineering, Applied Math, Computer Science, Chemistry or a related field.

  • A strong publication record in the peer-reviewed scientific literature
  • Demonstrated experience communicating results at national/international conferences
  • Ability to work independently and in teams to deliver high-quality results within aggressive timelines.
  • Well-versed in quantum chemistry and related softwares, e.g. Gaussian.
  • Strong background in statistics, regression, uncertainty analysis, and/or machine learning
  • Fluency In at least one scientific programming language (Python, MATLAB, R, etc.)