Postdoctoral Research Associate - Structural Simulation and Machine Learning; ML Polymer Compos

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice.

These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

We are seeking a Postdoctoral Research Associate who will support the Composites Innovation Group in the Manufacturing Science Division (MSD), Energy Science and Technology (ESTD) at Oak Ridge National Laboratory (ORNL) to support the composite manufacturing technologies through machine learning and physics-based simulations, specifically finite element analysis (FEA) for polymer composites. The candidate will also focus on developing a manufacturing process optimization framework for polymer composites through physics-based simulations, sensors from machines, and artificial intelligence.

Our research division carries out high quality R&D focused on the strategic composite material needs of the aerospace, automotive, and marine/shipbuilding industries as well as trending areas of international composite research in material science, mechanical and chemical engineering, and automation. The successful candidate will conduct research in the area of polymer composite manufacturing, specifically on the process optimization for the advancement of current manufacturing technologies, the development of the optimization framework, and the implementation of new optimization technologies.

• Develop Finite Element Method (FEM) models and Machine Learning (ML) codes for Multiphysics simulations with coupled thermal and electromagnetic modules.
• Develop in-house software for pre- and post-process of Multiphysics simulations with coupled thermal, mechanical, and electromagnetic modules for world-leading high-performance computing platforms.
• Perform large-scale multi-physics and multi-scale simulations involving heat transfer, mechanical deformation, and electromagnetics modeling for various composite manufacturing processes and complex industrial components.
• Develop and support the integration of a simulation-assisted process monitoring and control system for thermoplastic welding.
• Model ultrafast radio frequency heating for thermoplastic welding.
• Utilize machine learning algorithms to develop process optimization framework for polymer composite manufacturing.
• Utilize various types of sensors and analyze the data from manufacturing equipment.
• Utilize advance constitutive models and simulation tools for polymer composite analysis.
• Interface with other researchers and technical staff regarding simulation, production, and characterization of the materials.
• Publish original peer reviewed research articles.
• Write invention disclosures and reports.
• Supervise students/interns.
• Present and report research results and publish scientific results in peer-reviewed journals in a timely manner.
• Ensure compliance with environment, safety, health, and quality program requirements.
• Maintain strong dedication to the implementation and perpetuation of values and ethics.
• Ensure compliance with ORNL operation excellence.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace – in how we treat one another, work together, and measure success.

• A PhD in Materials Science and Engineering, Mechanical Engineering, Polymer Science and Engineering, or a related field completed within the last 5 years.
• Expertise in computational solid mechanics.
• Experience in polymer composite manufacturing.

• Prior knowledge and experience in developing…