Postdoctoral Research Associate - Large-Scale Simulations for Additive Manufacturing

UT-Battelle; Oak Ridge (TN); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Relocation Assistance

Educational Assistance

Wellness Programs

Employee Discounts

Job summary

UT-Battelle in Oak Ridge, TN, invites applications for a Postdoctoral Research Associate to advance multiphysics simulations and ML methods for additive manufacturing, virtual manufacturing, and material characterization.

The selected candidate will join the Multiscale Materials (MsM) group in the CSED, developing AI models, uncertainty quantification, and scalable numerical methods with collaboration across disciplines. Appointment up to 24 months; visa sponsorship not available.

Qualifications

• PhD in mechanical engineering, materials science, welding engineering or related field with emphasis on computational modeling and simulations within the past 5 years.
• Expertise in 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.

Responsibilities

• Collaborate within a multi-disciplinary research environment with computational scientists, computer scientists, experimentalists, and engineers/physicists.
• Participate in the development of multi-physics simulations with 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 and present at large forums.

Skills

Multi-physics simulations

Digital twin

Surrogate models

Machine learning

Interpersonal skills

Education

PhD in mechanical engineering, materials science, welding engineering or relevant field

Tools

FEM

Multi-physics codes

ML tools

Job description

Overview

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 resides in the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL). CSED focuses on 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 to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes.

Requisition Id 16802

Introduction to the MsM Group

The candidate will be a postdoctoral researcher within the Multiscale Materials (MsM) group of the Advanced Computing Methods for Physical Sciences Section in CSED. The MsM group is focused on delivering multiscale, multi-fidelity computational models and systems using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. The MsM group also develops artificial intelligence (AI) and foundational ML models to accelerate multiscale materials and flow sciences.

Major Duties/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 as well as represent the organization by giving technical presentations in large public forums.
  

Basic Qualifications

• A 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.
  

Preferred 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. Initial appointments and extensions are subject to performance and availability of funding.

• Export control, no clearance: 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: Visa sponsorship is not available for this position.

About ORNL

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up 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 are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following:

• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email [e-mail].

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.