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Computational Fluid Dynamics Specialist
2 months ago
The Multiphysics Computation Section at Argonne National Laboratory is seeking a highly skilled postdoctoral researcher to join our team. The successful candidate will contribute to cutting-edge research in low-carbon fuel injection and engine modeling, working closely with a multidisciplinary team of experts in computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML).
Key Responsibilities- Develop and implement advanced CFD models to simulate complex systems involving low-carbon fuel injection, turbulent combustion, and heat transfer.
- Perform high-fidelity simulations of combustion engines, focusing on fuel sprays, spray-wall interaction, and fuel-air mixing.
- Collaborate with experimentalists, CFD experts, and computational scientists to develop and integrate new models and simulations on next-generation supercomputing architectures.
- Contribute to the development of predictive capability and scalability of multi-scale and multi-physics simulation codes.
- Present and publish research results in peer-reviewed society technical reports and journal articles.
- Ph.D. in mechanical/aerospace engineering, applied mathematics, chemical engineering, or a related discipline earned within the past three years.
- Experience in modeling and simulation of three-dimensional multiphase turbulent reacting flow applications using 3-D CFD codes.
- Excellent understanding of sprays, spray-wall interaction, turbulence, chemical kinetics, reacting flow physics, and turbulent combustion modeling.
- Extensive knowledge of fuel properties and their effects on fluid behavior in reacting and non-reacting flow applications.
- Understanding of combustion engine theory and modeling.
- Strong collaborative and communication skills, with the ability to work effectively with diverse teams and stakeholders.
- Knowledge of and experience with modeling alcohol-based, bio-, and renewable fuels.
- Experience in geometry manipulation with computer-aided design software.
- Experience with coupling CFD and FEA codes.
- Knowledge of multi-dimensional code development for two-phase/multiphase flow and turbulent combustion applications.
- Knowledge of deep machine learning for multi-fidelity modeling and parallel scientific computing.
The successful candidate will join a dynamic and collaborative research team at Argonne National Laboratory, a leading institution in the field of energy and environmental research. The position offers opportunities for professional growth and development, as well as a chance to contribute to cutting-edge research in low-carbon fuel injection and engine modeling.
