Postdoctoral Research Associate

About the Role

We are seeking a Postdoctoral Research Associate for 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. This position is within the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL).

Key Responsibilities

• Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, and engineers/physicists conducting basic and applied research.
• 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 & Tech Stack

• PhD degree in mechanical engineering, material science, welding engineering, or a relevant engineering field with emphasis on computational modeling and simulations 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 skills, written and oral communication skills, and strong motivation.
• 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.

Qualifications

• 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 funding availability.
• This position requires access to technology that is subject to export control requirements.
• Visa sponsorship is not available for this position.
• Must be able to obtain and maintain a federal Personal Identity Verification (PIV) card, which requires a favorable post-employment background investigation, including a declaration of illegal drug activities.