Postdoctoral Research Associate - Data Science for Materials Characterization

Requisition Id 16197 

­­Overview:  

We are accepting applications for a Postdoctoral Research Associate position who will focus on the intersection of material science, materials characterization, and data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes.  This position resides in the Manufacturing Systems Analytics (MSA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD), at Oak Ridge National Laboratory (ORNL).

 

Major Duties/Responsibilities: 

• Develop algorithms and software tools for visualizing and analyzing materials characterization data
• Develop novel, data-driven materials characterization workflows
• Advance understanding of process-structure-property relationships via digital manufacturing practices
• Basic experience with AI/ML techniques
• Publish research in peer reviewed journals and conferences
• Support R&D staff members on their projects
• General support of research and development needs within the MDF
• 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 Ph.D. in material science, or closely related field with an emphasis on material science or characterization completed within the last five years
• Strong background in materials characterization techniques, such as microscopy, XRD, EBSD, and X-ray CT
• Interest in working at the intersection of material science, advanced manufacturing, and digital manufacturing
• Programming skills using Python or modern C/C++/C#
• Demonstrated experience conceiving and executing research and development projects
• The ability to work in a very dynamic team environment is required
• Excellent verbal and written communication skills

 

Special Requirements:

• Visa sponsorship is not available for this position

 

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 can 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:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

 

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.

 

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 individua