R&D Associate - Advanced Manufacturing and Characterization of Polymer Composites

Requisition Id16652

Overview:

We are seeking an R&D Associate Staff - Advanced Manufacturing and Characterization of Polymer Composites who will lead and execute research focused on experimental, computational modeling, and the establishment of processing-structure-property relationships for advanced polymer composite systems. The successful candidate will support the development of predictive tools, digital manufacturing capabilities, and data-driven approaches to accelerate the design, optimization, and scale-up of high-performance composite manufacturing processes. This position resides in the Composites Innovation Group within the Manufacturing Science Division, Energy Science and Technology Directorate, at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities:

• Conduct independent and team-based research on processing-structure-property relationships to enable the integration of novel polymer composite materials into advanced manufacturing workflows.
• Develop and apply high-rate manufacturing processes for composites including injection molding (IM), compression molding (CM), thermoforming, and sheet molding compound (SMC).
• Lead and manage multifunctional materials research projects, including planning, execution, and delivery of technical milestones.
• Conduct research on high-rate manufacturing of polymer composites for industrially relevant applications.
• Lead the development and application of computational modeling, simulation, and data-driven tools for advanced composite manufacturing processes and structures.
• Develop software, coding frameworks, and digital workflows for process modeling, material behavior prediction, design optimization, and manufacturing decision support using languages such as Python, MATLAB, C++, or similar platforms.
• Perform research on physics-based, data-driven, and hybrid modeling approaches for composite manufacturing processes, including additive manufacturing, joining, molding, and multifunctional materials.
• Support the development of digital twins, machine learning, artificial intelligence, and predictive analytics capabilities for advanced manufacturing systems and composite structures.
• Design and execute experimental validation activities to verify and improve modeling and simulation tools, including correlation of mechanical, thermal, microstructural, and manufacturing process data.
• Utilize advanced characterization and testing methods to generate validation datasets and establish processing-structure-property-performance relationships for composite materials and manufacturing processes.
• Perform failure analysis and process-property correlation to guide material and process improvements.
• Maintain high scientific productivity through collaboration, innovation, and research excellence.
• Engage with senior scientists, academic partners, and industry collaborators, and prepare technical reports, publications, and invention disclosures.
• 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, Polymer Science, Aerospace Engineering, or a related discipline.
• 2 years of post-PhD research or equivalent industrial R&D experience in polymer composites or advanced manufacturing.
• Proven ability to lead technical tasks and contribute to multidisciplinary research programs.

Preferred Qualifications:

• Experience leading experimental development, test planning, and validation strategies for composite manufacturing processes.
• Experience with high-rate composite manufacturing and scale-up research.
• Experience with injection molding, compression molding, thermoforming, SMC, and overmolding processes.
• Strong programming and software development skills (e.g., Python, MATLAB, C++, Julia, or similar) for engineering analysis, process modeling, data analytics, and automation.
• Experience with finite element analysis (FEA), process simulation, digital twins, machine learning, artificial intelligence, or physics-informed modeling applied to composite systems.
• Experience developing, validating, and deploying software tools and computational frameworks for advanced manufacturing applications.
• Background in multifunctional materials and advanced material characterization techniques.
• Experience with failure analysis and process-property correlation.
• Demonstrated record of peer-reviewed publications, technical reports, or patents.
• 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.

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.

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 ORNLRecruiting@ornl.gov.

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.