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Energy & Materials Intern — Materials Representation Learning for Accelerated Design

Toyota Research Institute
Los Altos, California
Internship
Posted January 14, 2026
$45 - $65/hr
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Application opens on company website

Job Description

This internship involves developing and evaluating machine learning-based material representations to accelerate materials design, focusing on integrating signals from various characterizations and properties to support property prediction and inverse design workflows in the field of materials science.

Key Responsibilities

  • Collaborate with researchers to prototype, evaluate, and implement representation-learning approaches for materials science.
  • Develop and integrate signals from multiple characterizations and computed properties into material representations.
  • Support the development of models for forward property prediction and inverse design workflows in materials research.

Requirements

  • Thrive at the intersection of machine learning and materials science and be motivated to develop the next generation of material representations integrating signals from multiple characterizations and measured computed properties to support accelerated materials design.
  • Collaborate with TRI researchers to prototype, evaluate, and ship representation-learning approaches that can serve as a foundation for forward property prediction and inverse design workflows.
  • Be available for a summer 2026 paid 12-week internship opportunity.
  • This internship must be an in-office role at Toyota Research Institute.
  • Provide a full list of publications via a link to Google Scholar when submitting your CV for this position.

Benefits & Perks

Paid 12-week summer internship
Hourly pay between $45 and $65 depending on factors
Medical insurance
Dental insurance
Vision insurance
Paid time off including holiday pay and sick time
In-office work environment

Ready to Apply?

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