Postdoctoral Research Associate - Computational Solid Mechanics for Digital Cert/Qual

Oak Ridge National Laboratory • Oak Ridge, TN

4d • Onsite

About The Position

We are seeking a Postdoctoral Research Associate who will use multiscale modeling and simulation to develop probabilistic lifing frameworks 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) applied to fatigue and ductile fracture is preferred. You will be expected to collaborate with research staff and industry partners to support certification and qualification efforts for components produced by various advanced manufacturing processes. This position resides in the Deposition Science and Technology Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL).

As part of our research team, you will engage with researchers of 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 industries. You will also be involved in proposal writing with our scientists while taking the lead in publishing high impact papers.

Requirements

• Ph.D. in materials science and engineering, mechanical engineering, or a field relevant to the job duties within the past 5 years.
• A strong background in mechanical behavior of materials is required.
• Experience in the development and implementation of constitutive models within commercial and/or open-source finite element software is required.

Nice To Haves

• 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 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.

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 probabilistic lifing approaches for additively manufactured materials using multiscale modeling.
• Present and report research results at workshops and conferences and publish key findings in peer-reviewed journals in a timely manner.
• 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.
• 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.

Benefits

• medical and retirement plans
• flexible work hours
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree