The Multi-Physics Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee on the topic of industrial burner CFD modeling. The successful candidate will leverage high-performance computing (HPC) resources at the Laboratory to perform CFD simulations of complex industrial burner systems involving modeling of low-carbon fuel injection and mixing, turbulent combustion, heat transfer, combustion, and emissions.

The successful candidate’s research will involve synergistic collaborations within a multidisciplinary team comprised of fellow postdoctoral appointees and staff scientists with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes.

• Develop accurate and computationally efficient CFD models and perform simulations of the entire chain of physics and chemistry involved with fuel-air mixing, turbulent combustion, heat transfer, and emissions of industrial burners.

• Perform high-fidelity reacting simulations that involve both conventional and low-carbon fuels, with emphasis on hydrogen and alcohol-based bio-fuels.

• Improve the computational efficiency and accuracy of physics-based and data-driven models for hydrogen/bio-fuel combustion in industrial burners.

• Work as a part of a multidisciplinary team involving experimentalists, CFD experts, and computational scientists to enable cutting-edge CFD modeling & simulations on the next generation supercomputing architectures.

Position Requirements

• Ph.D. in mechanical/aerospace/industrial engineering, applied mathematics, chemical engineering, or a related discipline earned no more than 3 years ago is required.

• Experience in modeling and simulation of three-dimensional multiphase turbulent reacting flow applications using 3-D CFD codes (e.g., CONVERGE, OpenFOAM, Ansys Fluent, etc.).

• Experience with modeling burners for industrial and/or residential applications.

• Experience with modeling combustion of both gaseous (natural gas, hydrogen) and liquid (alcohols) low-carbon fuels.

• Knowledge of industrial/residential burners operation.

• The candidate must demonstrate good collaborative skills, including the ability to work well with other divisions, laboratories, and universities, and communication skills at all levels of the organization.

• The successful candidate is expected to present and publish results in peer reviewed society technical reports and journal articles.

• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.

• Ability to make our laboratory a safe, welcoming, inclusive, and accessible environment where all can thrive.

Preferred Qualifications:

• Experience in modeling hydrogen/air flames for combustors/burners.

• Experience in geometry manipulation with computer-aided design software.

• Experience in carrying out research tasks with industry partners.

• Experience in interdisciplinary collaborative research.

• Knowledge of multi-dimensional code development (in C++/C/Fortran) and parallel scientific computing.

• Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and parallel scientific computing.

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