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Toyota Research Institute

Human-Centered AI Research Intern, Human – Computer Interaction

Los Altos, CA Remote Hybrid
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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 in Energy & Materials, Human-Centered AI, Human Interactive Driving, and Robotics.

This is a summer 2025 paid 12-week internship opportunity with the Future Product Innovation (FPI) team of the Human-Centered AI department at TRI. Please note that this internship will be a hybrid in-office role based in Los Altos, CA.

This internship opportunity falls within the Human-Centered AI Division (HCAI). We are an integrated team of ML researchers, behavior scientists, and human-computer interaction experts. At the core of our work, we aim to support people to make better decisions by maximising the best of big data, technology, and insights about why we do what we do.

The Team

The Future Product Innovation (FPI) team is an interdisciplinary team of researchers working at the intersection of generative artificial intelligence (AI), design, engineering, and creativity. Our mission is to accelerate design and engineering processes in the automotive industry. 

The Internship

We are seeking a highly motivated and dedicated PhD research intern to join our Future Product Innovation team and push the envelope on what is possible with Generative AI technologies in the domain of automotive product design. The ideal candidate will have a strong background in Human-Computer Interaction, Artificial Intelligence, or a related field, with demonstrated interest in exploring novel multimodal interaction techniques at the intersection of design, generative AI, and human-AI interaction. In this project, the intern will develop creativity support tools that facilitate the process of translating user’s psychological and emotional needs, such as “luxury” and “sporty”, into concrete product parameters in early stage concept design.

We will match the intern with mentors based on their experience. Over the course of the project, in addition to Future Product Innovation group meetings, the intern will also participate in all Human-Centered AI division meetings. The intern will be exposed to how interdisciplinary industrial research works and learn from our team as well as the other interns in our division. Furthermore, the intern will engage in strategy discussions about how their research connects to business impact at Toyota.

In collaboration with your mentor and the other researchers in the department, you will:

Responsibilities

  • Scope the project to align to the core research efforts
  • Be the primary driver of the technical plan (e.g., study design, model development, analysis plan) with regular feedback from mentors
  • Implement the project using TRI resources
  • Present the project’s approach and findings in research meetings
  • Our goal is that you end the summer with work that is publishable in an academic journal or conference

Qualifications

  • Currently enrolled in a PhD program in Human-Computer Interaction, Artificial Intelligence, or a related field
  • Demonstrated interest in exploring novel techniques at the intersection of design, generative AI, and human-AI interaction
  • Experience developing generative AI applications that leverage open-source LLMs, VLMs, and diffusion models (e.g. Stable Diffusion)
  • Experience designing and conducting user studies, analyzing data, and presenting research findings
  • Track record of driving and completing research projects, including publications at top conferences
  • Desire to work on challenging open-ended research projects
  • Demonstrated ability to work autonomously while soliciting feedback
  • Excellent communication and teamwork skills

Preferred Qualifications

  • Experience with modern front-end development frameworks (e.g., React)
  • Experience developing steerable AI applications with subjective attributes (e.g., luxury, sporty) and/or style preference data
  • Experience adapting pre-trained models to specific tasks or domains through fine-tuning or similar techniques
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.

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.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
Toyota Research Institute
Toyota Research Institute
Artificial Intelligence (AI) Automotive Consumer Research Machine Learning Product Research

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