Postdoctoral Research Associate - AI and CFD

Requisition  Overview

The Nuclear Energy and Fuel Cycle Division (NEFCD) of Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to assist in the development, qualification, and deployment of AI agents and models, Computational Fluid Dynamics (CFD) simulation codes, and Finite Element Method (FEM) based tools for nuclear energy (fission and fusion) applications. The position is part of the Multiphysics CFD Applications group, focusing on the development and application of models and simulations for energy production and nuclear systems.

• Conduct research and develop next-generation CFD methods (with finite volume and finite element techniques) and models for a variety of nuclear energy systems, using world-leading high-performance computing platforms.
• Perform large-scale simulations of fission and fusion systems employing models for turbulence, heat transfer, magnetohydrodynamics, etc.
• Employ finite element tools for tritium transport simulations in fusion devices.
• Support coordinated multi-physics simulations of fission reactor core, fusion device blankets, and other system components.
• Develop reduced-order calibration approaches and apply machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development.
• Complete simulation verification, model validation, uncertainty quantification, and documentation.
• Optimize system and component designs for performance and safety.
• Develop agentic workflows for scientific computing.
• Author peer-reviewed papers, technical reports for internal and external release and represent the organization by giving technical presentations to DOE program managers and in large public forums.

• A PhD or equivalent experience in nuclear, mechanical, or chemical engineering, engineering physics, or related field completed within the last 5 years.
• Experience with Python, C, and/or C++ applied programming.
• Demonstrated experience in applying and extending CFD codes for application to nuclear, or similarly complex, thermal energy systems.
• Experience with open-source CFD codes such as OpenFOAM or Nek
  5000, and/or commercial CFD codes such as STAR-CCM+, ANSYS or COMSOL.
• Knowledge of finite element simulations methods.
• Experience using parallel Linux computing platforms, parallel job submission scripts, common software repository tools (e.g., Git Hub), and parallel visualization software (e.g., Paraview).

• Exposure to developing agentic workflows.
• Code development using Git repositories, GPU computing.
• Development of agentic workflows for scientific applications.
• AI methods for CFD and FEM; multiphysics code integration.
• Experience with open-source fusion engineering codes (FESTIM, VertexCFD, OpenMC, etc).
• Excellent written and oral communication skills Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory.
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.

Applicants with a Ph.D. or equivalent experience obtained no more than five years prior to the date of application, and who have fulfilled all degree requirements before starting the appointment, are eligible. The appointment will initially be for up to 24 months, with the possibility of extension based on performance and funding availability.

This position requires the ability to obtain and maintain an HSPD-12 PIV badge. For employment at Oak Ridge National Laboratory (ORNL), a Real  form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.

To obtain this credential, new employees must successfully…