Computational Scientist, Large-scale Simulations and Machine Learning

Requisition Id 15757 

­­Overview:  

We are seeking a Computational Scientist for the Multiscale Materials group in the Computational Science and Engineering Division (CSED).  The candidate will be expected to contribute to the development and application of advanced manufacturing simulations, and machine learning (ML) models relevant to additive manufacturing, virtual manufacturing, material characterization, topology optimization, and real-time sensing. 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.

The candidate will be a research and development staff 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 algorithms for modeling and optimizing of metallic materials and advanced manufacturing processes.
• Participate in the design of integrated, scalable numerical methods and uncertainty quantification, and 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, or a relevant engineering field with emphasis on computational and material science. 2 years of applicable experience outside of Ph.D.
• Expertise in the development and application of multi-physics simulations and machine learning tools in one or more areas such as melt pool fluid dynamics, distortion and residual stress prediction, microstructure quantification, topology optimization, and surrogate and reduced-order models.
• Experience working in a multi-disciplinary research environment.
• Proven publication track record.
• Effective interpersonal skills, written and oral communication skills, and strong motivation.

Preferred Qualifications:

• Demonstrated experience in the design and implementation of numerical simulations and machine learning algorithms in one or more areas within advanced manufacturing processes.
• Demonstrated experience in the design and implementation of numerical algorithms in one or more high-level computing languages, preferably within a team that follows software quality standards.
• 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: 

Letters of Recommendation: 3 number of references are required.

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to ORNLRecruiting@ornl.gov the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• 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.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov.

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.

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.