Postdoctoral Appointee – Gas Turbine Modeling
Job posting number: #7208878 (Ref:417128)
Posted: January 20, 2024
The Multi-Physics Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing multi-physics and multi-scale CFD simulations of gas turbine engines. The candidate will be a part of the Transportation and Power Systems Division within the Advanced Energy Technologies Directorate at Argonne. The successful candidate’s research will involve collaborations with a multidisciplinary team involving computational fluid dynamics experts, gas turbine modelers and experimentalists to enhance the predictive capability of gas turbine modeling codes for stationary power generation and propulsion applications.
The candidate will perform multi-fidelity CFD simulations of gas turbines using alternate fuels including hydrogen and hydrogen carriers by further developing in-house and commercial codes, leveraging high-performance computing (HPC) and develop Reduced-Order Models for predicting rare events such as flame flashback, and blow out.
Perform high-fidelity simulations of gas turbine combustors with gaseous fuels for stationary power generation applications. Focus on de-carbonization of this sector via the use of Carbon-less and low-Carbon fuels.
Develop machine learning based reduced-order models for predicting rare events including flame flashback.
Work as a part of a multidisciplinary team involving experimentalists, Computational Fluid Dynamics (CFD) experts and computational scientists to run the simulations using the next generation supercomputing architectures.
Present and publish results in peer reviewed society technical reports, journal articles, and meetings with key stakeholders.
Ph.D. in Mechanical/Aerospace engineering, chemical engineering, applied mathematics, or a related discipline and should be 0 – 3 years post Ph.D.
Knowledge of gas turbine combustion theory of operation.
Knowledge of liquid and gaseous fuels for gas turbine applications.
Experience in the use of ML softwares (TensorFlow, PyTorch, Julia, etc.) for reduced-order modeling and simulations, CFD, management and analysis of big data, and parallel scientific computing.
Ability to collaborate and work well with other divisions, laboratories, universities, and industry.
Skilled verbal and written communication skills 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.
Understanding of turbulence, chemical kinetics, reacting flow physics, and combustion modeling.
Experience in simulation of turbulent reacting flows in gas turbine combustors using CFD codes (e.g., CONVERGE, OpenFOAM, CharLES etc.).
Experience with high-order CFD methods and solvers.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull 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.
Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.