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Postdoctoral Appointee – CFD Modeling of Industrial Burners
4 months ago
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.
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full time