Description
Overview:
We are seeking a Postdoctoral Research Associate – Simulation and Machine Learning for Composite Manufacturing who will focus on developing physics-based simulation and machine-learning-driven optimization frameworks for polymer composite manufacturing processes. This position resides in the Composites Innovation Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD), at Oak Ridge National Laboratory (ORNL).
Major Duties/Responsibilities:
Develop physics-based computational models, including Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD), for polymer composite manufacturing processes
Perform multi-physics simulations involving coupled thermal, mechanical, and material behavior across multiple length scales
Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control
Integrate simulation tools with in-situ sensor data from manufacturing systems to enable simulation-assisted process monitoring and control
Support research on advanced composite manufacturing processes such as thermoforming, compression molding, injection molding, and automated fiber placement
Apply advanced constitutive material models for polymer composite behavior under processing conditions
Collaborate with multidisciplinary research teams on simulation, manufacturing, and material characterization efforts
Supervise students and interns supporting modeling and data analysis tasks
Prepare technical reports, invention disclosures, and peer-reviewed publications
Present research findings at conferences, program reviews, and technical meetings
Ensure compliance with environmental, safety, health, and quality program requirements
Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.
Basic Qualifications:
A PhD in materials science and engineering, mechanical engineering, aerospace engineering, polymer science, or a related discipline completed within the last five years.
Demonstrated expertise in computational mechanics and numerical modeling
Experience in polymer composite manufacturing processes
Experience with simulation tools for thermomechanical analysis
Programming experience in scientific computing environments
Preferred Qualifications:
Experience developing Finite Element Method or CFD models for composite manufacturing applications
Knowledge of machine learning algorithms for engineering systems
Programming experience in FORTRAN, C, or C++ and scripting experience in Python or similar languages
Experience with parallel computing environments and Linux-based systems
Background in topology optimization and structural design
Experience in thermomechanical characterization of polymer materials
Demonstrated experimental capabilities and a strong understanding of experimental design, test planning, and data interpretation for polymer composite manufacturing processes, including the ability to translate modeling results into validation experiments and process development strategies.
Familiarity with sensors and data acquisition systems in manufacturing environments
Strong record of peer-reviewed publications
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.
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.
Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to Postdocrecruitment@ornl.gov) with the position title and number referenced in the subject line.
Instructions to upload documents to your candidate profile:
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Under the My Documents section, select Add a Document
Security, Credentialing, and Eligibility Requirements
For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant 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 complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
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, and Employee Discounts.
