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The Multi-Physics Engine Computation Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee. The successful candidate will engage in collaborative research within a multidisciplinary team comprising engine modelers, CFD and AI/ML experts, and computational scientists. The primary focus will be on enhancing the predictive capability and scalability of multi-scale and multi-physics simulation codes.
The candidate will conduct multi-physics and multi-scale computational fluid dynamics (CFD) simulations for innovative internal combustion engines (ICEs) fueled with low/zero-carbon fuels and utilized in combined heat and power systems, leveraging high-performance computing (HPC) resources. Responsibilities include:
Executing high-fidelity CFD simulations of ICEs’ in-cylinder processes, encompassing gaseous fuel injection, turbulent jet ignition, turbulent combustion, pollutant formation, and heat transfer phenomena.
Optimizing combustion chamber geometry and operational parameters of ICEs to enhance thermal efficiency, throughput, and minimize emissions.
Enhancing and developing CFD submodels in commercial CFD codes like CONVERGE to improve simulation predictive capability.
Position Requirements
A Ph.D. in mechanical/aerospace engineering, chemical engineering, or a related discipline earned within the last three years.
Knowledge in CFD modeling of turbulent reacting flows in advanced propulsion and energy conversion systems using CFD codes (e.g., CONVERGE, STAR-CD, OpenFOAM, etc.) is essential.
In-depth understanding of combustion theory and modeling for ICEs, extensive knowledge of advanced ignition and combustion concepts, as well as a solid grasp of turbulence and chemical kinetics.
Previous involvement in research collaborations with industry partners.
Skilled written and oral communication skills at all levels of the organization.
Demonstrated collaborative abilities, including effective teamwork across divisions, laboratories, and universities.
The successful candidate must embody and model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Preferred Qualifications:
Experience in multi-dimensional code development (in Fortran/C/C++) and parallel scientific computing on large-scale HPC platforms.
Job Family
Postdoctoral Family
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne’s Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
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