Postdoctoral Research Associate - Large-Scale Simulations for Additive Manufacturing

About the role

We are seeking a Postdoctoral Research Associate to join the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL). This position resides in the Multiscale Materials (MsM) group, which focuses on delivering multiscale, multi-fidelity computational models and systems using algorithms and analytics for materials and related physical sciences. The role involves the development and application of advanced multiphysics simulations and machine learning (ML) methods relevant to additive manufacturing (AM), virtual manufacturing, material characterization, topology optimization, and real-time sensing.

CSED drives transdisciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences and develops community applications, data assets, and technologies to build knowledge and impact in novel, crosscut-science outcomes.

Responsibilities

• Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, and engineers/physicists conducting basic and applied research in support of the Laboratory’s missions.
• Participate in the development of multi-physics simulations with machine learning (ML) methods for modeling and optimization of metallic materials and advanced manufacturing processes.
• Participate in the design of integrated, scalable numerical methods and uncertainty quantification.
• Follow team planning, documentation, verification and validation, and manufacturing-material-related simulation quality processes.
• Author peer-reviewed papers, technical papers, reports, and proposals for internal and external release.
• Represent the organization by giving technical presentations in large public forums.

Requirements

• A PhD degree in mechanical engineering, material science, welding engineering, or a relevant engineering field with emphasis on computational modeling and simulations, obtained within the past 5 years.
• Expertise in the development and application of multi-physics simulations, digital twin, surrogate and reduced-order models, and machine learning tools for part qualification and quantification of distortion, residual stress, microstructure, and fatigue.
• Effective interpersonal, written, and oral communication skills, and strong motivation.

Qualifications

• Demonstrated expertise in multi-physics simulations using Finite Element Methods (FEM) for part qualification and quantification.
• Demonstrated expertise in design and implementation of multi-physics codes for metal AM applications, including thermo-mechanical response as well as microstructure and phase transformation response.
• Demonstrated expertise in process development/optimization for digital twin, surrogate and reduced-order models, and ML/AI tools applied to macro-scale deformation in AM.
• Experience with multi-physics simulations on high-performance computing (HPC) and ML.
• Experience working in a multi-disciplinary research environment.

Special Requirements

• Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment.
• The appointment length will be up to 24 months with the potential for extension, subject to performance and availability of funding.
• This position requires access to technology that is subject to export control requirements. Successful candidates must be qualified for such access without an export control license.
• Visa sponsorship is not available for this position.
• Three letters of recommendation are required when applying to this position.

Benefits

• Competitive pay and benefits programs.
• Medical, dental, and vision plans.
• 401(k) Retirement Plan and Contributory Pension Plan.
• Life Insurance and Disability Benefits.
• Generous vacation and holidays, including parental leave.
• Legal Insurance with Identity Theft Protection.
• Employee Assistance Plan.
• Flexible Spending Accounts and Health Savings Accounts.
• Wellness Programs and Educational Assistance.
• Relocation Assistance and Employee Discounts.
• On-site fitness, banking, and cafeteria facilities.

About ORNL

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an 80-year legacy of addressing the nation’s most pressing challenges. Our team consists of over 7,000 dedicated and innovative individuals. Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles support our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.