Energy & Materials Intern- XRD Advanced Analysis
Quick Summary
At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience.
At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.
This is a paid 12-week internship opportunity and is a hybrid, in-office role.
Here’s a glimpse into the Internship experience from some of our TRI interns!
The intern will work within the AMDD team on a project focused on developing advanced analysis tools and pipelines for X-Ray diffraction (XRD) patterns of mixed-metal oxide thin-films. They will use and develop automated Rietveld refinement tools to label XRD patterns and understand structure-property-processing relationships across a compositionally diverse dataset. They will perform phase identification on XRD patterns ranging from unary to ternary metal-oxides, and develop pipelines to perform automatic or human-assisted labeling of experimental data. They will investigate crystallite size, texturing, and strain across the dataset. This work will contribute to the development of automated workflows for phase identification from XRD, an essential bottleneck in accelerating high-throughput materials discovery.
Scope the project to align with the core research efforts.
Be the primary driver of the technical plan (e.g., model development, analysis plan) with regular feedback from mentors.
Execute the project using TRI resources.
Present the project’s approach and findings in research meetings.
Pursuing a PhD in Materials Science, Chemistry, Physics, or related fields.
Familiar with running tabletop or synchrotron XRD experiments.
2+ years experience in performing Rietveld refinement, bonus if familiar with analyzing different materials classes.
Experience with basic data analysis in Python.
A track record of executing research projects evidenced by journal publications.
Strong communication skills and ability to work and foster collaboration across interdisciplinary teams.
Desire to work on challenging and open-ended research projects.
Experience using XRD phase identification software, e.g. DARA, GSAS-II, MAUD, Spotlight.
Experience working with thin-film metal oxides.
Comfortable working with large datasets.
Experience with code best practices and collaborative software development using git.
Location & Eligibility
Listing Details
- Posted
- June 18, 2026
- First seen
- June 18, 2026
- Last seen
- June 19, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 70%
- Scored at
- June 18, 2026
Signal breakdown
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