Postdoctoral Appointee - Modeling Engine Combustion

Argonne National Laboratory
Lemont, IL
Closing date
Feb 4, 2023

View more

Organization Type
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, ignition, and combustion processes for 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.

Position Requirements

* 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 and liquid sprays injection modeling.
* Experience in geometry optimization with computer-aided design software.

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.

Please note that all Argonne employees are required to be vaccinated against COVID-19. All successful applicants will be required to provide their COVID-19 vaccination verification as a condition of employment, subject to limited legally recognized exemptions to COVID-19 vaccination.

Get job alerts

Create a job alert and receive personalized job recommendations straight to your inbox.

Create alert