Postdoc: Materials Data Science for Digital Manufacturing

Oak Ridge National Laboratory; Knoxville (TN); On-site; USD 60,000 - 80,000; Full time

Job summary

Oak Ridge National Laboratory's Manufacturing Systems Analytics (MSA) Group within the Manufacturing Science Division invites applications for a Postdoctoral Research Associate focusing on data science for materials characterization. The role spans material science, characterization, and digital manufacturing to develop new methodologies for assessing quality in components made by advanced processes.

The successful candidate will publish in peer-reviewed venues, contribute to AI/ML approaches,

Qualifications

• Ph.D. in materials science or closely related field completed within the last five years.
• Strong background in materials characterization techniques (microscopy, XRD, EBSD, X-ray CT).
• Interest in intersection of material science, advanced manufacturing, and digital manufacturing.
• Programming skills in Python or modern C/C++/C#.
• Experience conceiving and executing R&D projects.
• Ability to work in a very dynamic team environment.
• Excellent verbal and written communication skills.

Responsibilities

• Develop algorithms and software tools for visualizing and analyzing materials characterization data.
• 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.

Skills

Python

C/C++

C#

Materials characterization

Education

PhD in Materials Science

Tools

XRD

EBSD

X-ray CT

Job description

Oak Ridge National Laboratory's Manufacturing Systems Analytics (MSA) Group within the Manufacturing Science Division invites applications for a Postdoctoral Research Associate focusing on data science for materials characterization. The role spans material science, characterization, and digital manufacturing to develop new methodologies for assessing quality in components made by advanced processes.

The successful candidate will publish in peer-reviewed venues, contribute to AI/ML approaches,