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 Robotics, Human-Centered AI, Human Interactive Driving, and Energy & Materials.
The Energy & Materials Division is accelerating Toyota’s path to carbon neutrality. Your activities will support the Accelerated Materials Design and Discovery (AMDD) program, which aims to accelerate the discovery of new materials and devices for batteries, fuel cells, and more. Our research merges materials simulations, new experimental data, artificial intelligence, and automation. We collaborate closely with universities, national labs, and colleagues across global Toyota. AMDD seeks to develop and translate the newest technologies into practice, both within Toyota and across the open research community more broadly.
We are looking for a graduate resident who can help us develop innovative AI solutions to accelerate real materials discovery. This is a full-time program (9-12 months long) where you will have the opportunity to work collaboratively with us on a project to translate the latest AI techniques into the materials science domain. You will craft novel architectures to integrate multi-modal data from both simulations and experiments. We regularly present our work at conferences, engage with the Toyota family of companies, patent our innovations, and publish papers in peer-reviewed venues.

Responsibilities

• Translating and crafting new ML architectures for the materials science domain.
• Software engineering with rapid and accurate code development, in frameworks such as PyTorch.
• Scaling up training and inference (machine learning engineering).
• Composing research results in the form of an academic paper, conference presentation, and open-source projects.

Qualifications

• Master's degree or currently enrolled in a graduate program in computer science, statistics, materials science, physics, or a related field.
• Hands-on experience with current deep learning frameworks (PyTorch, TensorFlow, etc.), as evidenced by released code (e.g. on GitHub or elsewhere).
• Have a strong research background, including at least one publication in a peer-reviewed venue
• Thrive in a culture that values diversity, teamwork, modesty, and learning.

Bonus Qualifications

• Experience with multimodal models and/or materials science applications

The pay range for this position at commencement of employment is expected to be between $55 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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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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.