Associate Research Staff - Computational Solid Mechanics

Requisition Id 16330 

Overview: 

We are seeking a Research Associate who will support the Deposition Science and Technology (DSaT) Group in the Manufacturing Science Division (MSD) at Oak Ridge National Laboratory (ORNL).   MSD resides in the Energy Science and Technology Directorate (ESTD). DSaT performs research and development on the processing of metallic material systems for extreme environment and high temperature applications. The Research Associate will contribute to the development of thermo-mechanical modeling tools to support process development for advanced manufacturing processes and of process-microstructure-property-performance relationships for high-temperature alloys and extreme environment structural materials. A strong background in mechanical behavior of materials is required.  Demonstrated experience in the implementation of nonlinear constitutive models in commercial (e.g. Abaqus, ANSYS, etc.) and/or open-source finite element (FE) codes (e.g., MOOSE, DAMASK, etc.) is required.  Experience with microstructural modeling (e.g. crystal plasticity) and computational homogenization are preferred.  You will be expected to collaborate with research staff and industry partners in the development of multiscale modeling methods to support certification and qualification efforts for components produced by various advanced manufacturing processes.

 

As part of our research team, you will engage with researchers with various backgrounds (e.g., materials science, mechanical behavior of materials, heat transfer) and interact closely with industry partners. These engagements will play a vital role in ensuring success of programs and the adoption by project sponsors, and in developing your network across academia and industry. You will also be involved in writing and supporting the development of proposals while taking the lead in publishing high impact papers.

 

Major Duties/Responsibilities:

• Participate in the development and implementation of nonlinear constitutive models into FE codes.
• Participate in the development and implementation of crystal plasticity constitutive models into FE codes for additively manufactured alloys.
• Participate in the development of multiscale modeling approaches to establish process-structure-property-performance relationships for structural materials.
• Apply advanced manufacturing process simulation tools to understand and mitigate the development distortion and residual stress.
• Collaborate within a multi-disciplinary research environment consisting of computational scientists, experimentalists, and engineers conducting basic and applied research in support of the Laboratory’s missions.
• Present and report research results at workshops and conferences and publish key findings in peer-reviewed journals in a timely manner.
• Ensure compliance with environment, safety, health, and quality program requirements per ORNL’s Standards-Based Management System (SBMS).
• Maintain strong dedication to the implementation and perpetuation of institution values and ethics.
• Support senior staff in the development and execution of projects that provide valued and timely deliverables to the various stakeholders.
• 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:

• Ph.D. in materials science and engineering, mechanical engineering, or related field.
• Experience in the development and implementation of constitutive models within commercial and/or open-source finite element software.
• A background in mechanical behavior of materials.

 

Preferred Qualifications:

• Demonstrated expertise in multi-physics FE simulations is preferred.
• Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred.
• Excellent record of productive and creative research as demonstrated by publications in peer-reviewed journals.
• Excellent written and oral communication skills.
• Motivated self-starter with the ability to work independently, and to participate creatively in collaborative multi-disciplinary tea