Job Opportunity: Postdoctoral Appointee – CFD Modeling of Industrial Burners at Argonne National Laboratory

The Multi-Physics Computations group at Argonne National Laboratory is actively seeking a Postdoctoral Appointee specializing in industrial burner CFD modeling. This role offers an exciting opportunity to leverage high-performance computing (HPC) resources to perform complex CFD simulations of industrial burner systems.

Job Responsibilities

The successful candidate will:

• Conduct CFD simulations focusing on low-carbon fuel injection, turbulent combustion, heat transfer, and emissions.
• Develop precise and computationally efficient CFD models for the entirety of fuel-air mixing, turbulent combustion, heat transfer, and emissions in industrial burners.
• Perform high-fidelity simulations for both conventional and low-carbon fuels, with an emphasis on hydrogen and alcohol-based bio-fuels.
• Enhance the computational efficiency and accuracy of physics-based and data-driven models for hydrogen/bio-fuel combustion.
• Collaborate within a multidisciplinary team including experimentalists, CFD experts, and computational scientists to enable advanced CFD modeling and simulations on next-generation supercomputing architectures.

Position Requirements

• Ph.D. in mechanical/aerospace/industrial engineering, applied mathematics, chemical engineering, or a related discipline, earned within the last 3 years.
• Significant experience in modeling and simulation of three-dimensional multiphase turbulent reacting flow applications using 3-D CFD codes (e.g., CONVERGE, OpenFOAM, Ansys Fluent).
• Experience with burner modeling for industrial and/or residential applications.
• Knowledge of combustion modeling for gaseous (natural gas, hydrogen) and liquid (alcohols) low-carbon fuels.
• Familiarity with the operation of industrial/residential burners.
• Excellent collaborative and communication skills at all organizational levels.
• Proven ability to present and publish research results in peer-reviewed technical reports and journal articles.
• Alignment with Argonne’s core values of impact, safety, respect, integrity, and teamwork.
• Commitment to fostering a safe, inclusive, and accessible work environment where all team members can thrive.

Preferred Qualifications

• Experience in modeling hydrogen/air flames for combustors/burners.
• Proficiency in geometry manipulation with computer-aided design software.
• Experience in collaborative research tasks with industry partners.
• Interdisciplinary collaborative research experience.
• Knowledge in developing multi-dimensional code (C++/C/Fortran) and parallel scientific computing.
• Familiarity with deep machine learning (using TensorFlow, PyTorch) for multi-fidelity modeling, regression tasks, large datasets management, and parallel computing.

Job Details

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, Argonne National Laboratory is committed to fostering a diverse and inclusive workplace that drives collaborative scientific discovery and innovation. We encourage minorities, women, veterans, and individuals with disabilities to apply.

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, along with guest researchers and contractors, are subject to restrictions related to participation in Foreign Government Sponsored or Affiliated Activities. These restrictions will be reviewed by Argonne's Legal Department. All employment offers are contingent upon a background check, including criminal conviction history, customized per case.

Please note, this role may require obtaining government access authorization, which includes additional background check requirements. Failure to obtain or maintain such authorization may result in the withdrawal of a job offer or future employment termination.