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:
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