Energy & Materials Research Intern, Agentic Modeling
Los Altos, CA
Energy & Materials – Internships - Fall 2025 /
Intern /
Hybrid
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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics.
This is a Fall 2025/Winter 2026 paid 12-week internship opportunity in Los Altos, HQ. Please note that this internship will be an in-office hybrid role.
Energy & Materials
The Energy & Materials Division at TRI is building tools and creating strategies, from accelerating the design, discovery, and deployment of new materials to performing interdisciplinary systems analysis to help foster a transition to more sustainable mobility. Our research applies AI, data-driven methods, and automation to materials science and device engineering, along with stakeholder-informed systems modeling.
The Team
The long-term vision of TRI’s Accelerated Materials Design and Discovery (AMDD) program is to accelerate the development of truly emissions-free mobility. Realizing this vision will require the discovery of new materials and devices for batteries, fuel cells, and more. Our aim at TRI is to merge sophisticated computational materials modeling, new experimental data, artificial intelligence, and automation to significantly accelerate materials research in this area. Our focus is on developing tools and capabilities to enable this acceleration. We collaborate closely with a dozen universities and national labs and our colleagues across global Toyota. AMDD seeks to develop and translate the newest technologies into practice, both within Toyota and the open research community, more broadly.
The Internship
This project aims to develop methodologies for AI agents to acquire and document expert knowledge, thereby improving their capacity to plan, design, and execute complex tasks within scientific and engineering domains. The intern will showcase the practical application of these systems, with the goal of producing adaptable frameworks and advancing the understanding of agentic AI's contribution to scientific exploration and automation.
Qualifications
- PhD candidate in computer science, applied mathematics, materials science, engineering, physics, chemistry, or a related field.
- Familiarity with Large Language Models (LLMs) and agentic systems.
- Experience with fine-tuning LLMs, Retrieval-Augmented Generation (RAG), or one/few-shot prompting.
- Proficiency in computational workflow documentation and artifact generation.
- Ability to set up and experiment with LLMs and agentic systems locally.
- Analytical skills for assessing agent performance and critiquing recorded workflows.
- Aptitude for applying AI concepts to practical scientific and engineering problems.
- Excellent written communication skills for report writing and conference submissions.
- Familiarity with relevant tools and frameworks.
Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.
The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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