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Postdoctoral Appointee – Turbulent Reacting Flows and Machine Learning
Requisition Number: 409907 Location: Lemont, IL
Functional Area: Research and Development Division: ES-Energy Systems
Employment Category: Temporary 6 Months or Greater Education Required: Doctorate Degree
Level (Grade): 700 Shift: 8:30 - 5:00
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Develop machine learning (ML) frameworks for reduced-order modeling of chemical kinetics and turbulent combustion phenomena using High-Performance Computing (HPC) tools. Demonstrate the ML frameworks in Computational Fluid Dynamics (CFD) simulations of canonical and application-specific turbulent reacting flows. Import framework on leadership class supercomputing resources, and identify and improve the bottlenecks in scaling. Deploy the reduced-order models to accelerate high-fidelity reacting flow modeling and simulation.

The successful candidate’s research will involve synergistic collaborations with a multidisciplinary team involving turbulent reacting flow modelers, computational fluid dynamics experts, and computational scientists to enhance the predictive capability of multi-scale and multi-physics codes.

  • Ph.D. in mechanical/aerospace engineering, computer/data science, applied mathematics, chemical engineering, or a related discipline.  

  • Demonstrated background and experience in the development of deep learning algorithms and software (in TensorFlow, PyTorch, Julia, etc.) for reduced-order modeling and simulations, CFD, management and analysis of big data, and parallel scientific computing is required.

  • Understanding of turbulence, chemical kinetics, reacting flow physics, and combustion modeling is desired. Expertise in the development and application of machine learning tools in one or more of these areas is a plus.

  • Experience in simulation of turbulent reacting flows in energy conversion systems (e.g., internal combustion engines, gas turbine combustors, etc.) using CFD codes (e.g., CONVERGE, OpenFOAM, etc.) is desired. Experience with high-order CFD methods and solvers is a plus.

  • Knowledge of large scientific code management and optimization is desirable. Experience with GPU computing is a plus.

  • Collaborative skills, including the ability to work well with other divisions, laboratories, and universities.

  • Ability to demonstrate strong written and oral communication skills.

  • A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. 


What will put you ahead:

  • Experience in interdisciplinary collaborative research.

As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

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