[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Toyota Motor jobs](https://jobs.opennash.com/companies/toyota-motor/) · [Search jobs](/search/) Toyota Motor · Los Altos, CA # Accelerated Science Intern, Representation Learning for Molecules and Materials Los Altos, CA Internship or early career Early career $65/hour Education & Training Listed on Toyota Motor’s official careers site. Posted October 30, 2026. Check that it is still open and apply there. [Apply on Toyota Motor’s careers site →](https://jobs.lever.co/tri/9c851b9d-169d-4bb3-b164-828098e077e7) [OpenNash Jobs](https://jobs.opennash.com/) / [Toyota Motor](https://jobs.opennash.com/companies/toyota-motor/) / Accelerated Science Intern, Representation Learning for Molecules and Materials ## Job description 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 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 cutting-edge computational materials modeling, experimental data, artificial intelligence, and automation to significantly accelerate materials research. Our focus is on developing tools and capabilities to enable this acceleration. We collaborate closely with a dozen universities and national labs and 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 We’re looking for a researcher/engineer interested in how machine learning models represent molecules and materials, and whether different models discover the same underlying physical structure. In this role, you’ll collaborate with TRI researchers to investigate how training data, learning objectives, and model architectures shape learned representations. The work will combine mathematical reasoning with computational experiments to study when models arrive at shared representations, what information those representations capture, and how they connect to the physics of the systems being studied. ### Responsibilities Implement and evaluate machine learning models for molecules and materials using reproducible training and analysis workflows. Design controlled experiments to study how learned representations vary across training runs, model architectures, and learning objectives. Investigate the geometry and information content of learned representations and their relationship to physical quantities. Develop evaluation methods to distinguish meaningful shared structure from similarities introduced by model parameterization or analysis choices. Contribute high-quality, well-documented code to an internal codebase and help translate results into internal reports, publications, and/or patent disclosures (as appropriate). ### Qualifications Currently enrolled in a doctoral program in materials science, computer science, statistics, applied math, machine learning, physics, or a related discipline. Strong foundations in machine learning, linear algebra, probability, and optimization, with demonstrated experience training models on real datasets. Familiarity with representation learning or scientific machine learning; experience studying model convergence, learning dynamics, symmetries, or identifiability is a plus. Proficiency in Python and modern ML tooling (e.g., PyTorch, experiment tracking, reproducibility best practices). Ability to work collaboratively across disciplines and to translate research ideas into working code. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. ## At a glance - Posted by the employer: Oct 30, 2026 - First seen by OpenNash: Oct 31, 2026 - Last checked: Oct 31, 2026 - Listed for: 1 day - Location: Los Altos, CA - Employment type: Internship or early career - Pay: $65/hour[Apply on Toyota Motor’s careers site →](https://jobs.lever.co/tri/9c851b9d-169d-4bb3-b164-828098e077e7) ## Hiring at Toyota Motor - Open jobs: 307 - New in the last 7 days: 60 - Tracked since: Jul 18, 2026 [All Toyota Motor jobs](https://jobs.opennash.com/companies/toyota-motor/) · [Weekly hiring report](/reports/hiring/) ## More jobs at Toyota Motor ### [Postdoctoral AI Fellow, Post-Training for Materials Discovery](https://jobs.opennash.com/companies/toyota-motor/jobs/91e9606e7f99eeb8dfba/) Los Altos, CA ### [Robotics Intern, Post-Training and Continual Learning](https://jobs.opennash.com/companies/toyota-motor/jobs/268db390e1a7d90b6d23/) Los Altos, CA ### [Robotics Intern, Trustworthy Learning under Uncertainty](https://jobs.opennash.com/companies/toyota-motor/jobs/307000b6d6284d0f5a32/) Los Altos, CA ### [Executive Assistant](https://jobs.opennash.com/companies/toyota-motor/jobs/b6f1ee6bd9e2e6f7769e/) Los Altos, CA ### [Human Interactive Driving Intern – World Models](https://jobs.opennash.com/companies/toyota-motor/jobs/bfe751831b924e0fe6ad/) Los Altos, CA ## Similar jobs at other companies ### [2027 Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting](https://jobs.opennash.com/companies/amazon/jobs/ec62591ec9ad3128e879/) Amazon · US, WA, Seattle ### [Senior Machine Learning Engineer, Accelerated Apache Spark](https://jobs.opennash.com/companies/nvidia/jobs/ecff06cbb4e926d552af/) NVIDIA · US, CA, Santa Clara ### [General Manager Accelerated Trainee (GMAP)](https://jobs.opennash.com/companies/republic-services/jobs/64c9364d89f82ca5ec15/) Republic Services · Phoenix, Arizona ### [2027 Accelerated Development Program - Accounting & Finance](https://jobs.opennash.com/companies/trane-technologies/jobs/c3f43163b41c867c68b8/) Trane Technologies · Davidson, North Carolina, United States of America ### [2027 Summer Applied Science Internship - Information & Knowledge Management (Machine Learning)- United States, PhD Student Science Recruiting](https://jobs.opennash.com/companies/amazon/jobs/7128f74c5feed87f1056/) Amazon · US, WA, Seattle OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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