Postdoctoral Appointee – Heavy-Duty Engine Modeling
Job posting number: #7116440 (Ref:414455)
Posted: November 19, 2022
Application Deadline: Open Until Filled
The Multiphysics Engine Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee. The successful candidate’s research will involve synergetic collaborations with a multidisciplinary team involving engine modelers and experimentalists, and computational scientists to enhance the predictive capability of engine modeling codes.
Perform Computational Fluid Dynamics (CFD) simulations of fuel injection, mixing, and combustion processes for heavy-duty internal combustion engines using High-Performance Computing. Evaluate the impact of fuel properties and kinetics on combustion. Analyze advanced mixing and combustion methods for engines. Develop sub-models that improve CFD predictions and implement those models into commercial CFD codes. Use Machine Learning tools to gain further insights into complex datasets that are generated.
Candidates must have a Ph.D. in mechanical/aerospace engineering, applied mathematics, chemical engineering, or a related discipline.
Knowledge of multi-dimensional code development (in C++/C/Fortran) for turbulent combustion modeling, internal combustion engine theory and operation, and parallel scientific computing is required.
Knowledge of large scientific code management and optimization is desirable.
Collaborative skills, including the ability to work well with other divisions, laboratories, and universities.
Skilled in oral and written communications at all levels of the organization.
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 modeling non-reacting and reacting flows using CFD codes used by industry (e.g., CONVERGE).
Experience in gaseous fuels modeling.
Experience in geometry optimization with computer-aided design software.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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