Future Product Innovation Research Intern
Toyota Research Institute
This job at a glance
- Who can apply
- New grads and up to 1 year
- Must know
- LLMsStakeholder management
- Work
- On-site in Los Altos · internship
- Pay
- Not stated by the employer.
- Skill demand
- Stakeholder management41%LLMs11%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 11, 2026 · still open
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About the Role
Toyota Research Institute (TRI) is seeking a motivated PhD research intern to join the Future Product Innovation team within the Human-Centered AI Division (HCAI). The internship focuses on advancing Generative AI for product design, exploring how multimodal behavioral signals from user interactions can inform generative AI-driven product personalization and recommendation. This is a paid 12-week, hybrid, in-office opportunity.
Key Responsibilities
In collaboration with your mentor and other researchers, you will:
- Scope the project to align with core research efforts.
- Drive the technical plan, including model development and analysis, with mentor feedback.
- Execute the project using TRI resources.
- Present the project’s approach and findings in research meetings.
- Participate in Future Product Innovation group meetings, Human-Centered AI division meetings, and meetings with stakeholders from relevant Toyota business groups.
- Engage in strategy discussions connecting research to business impact at Toyota.
Requirements & Tech Stack
- Currently enrolled in a PhD program in Human Computer Interaction, Computer Science, or a related field.
- Experience analyzing behavioral signals (e.g., eye gaze, mouse interactions, verbal utterances, interaction logs) to infer and model user intent and preferences.
- Experience designing and developing interactive research prototypes for novel human-AI interaction paradigms.
- Experience designing and conducting human-subject studies, including collecting and analyzing behavioral interaction data using quantitative and/or qualitative methods.
- Proven track record of working autonomously while soliciting feedback.
- Proven track record of publications at top venues (e.g., CHI, UIST, IUI, UbiComp/IMWU).
- Strong interpersonal skills and a great teammate.
- Strong interest in interdisciplinary work.
Preferred Qualifications
- Experience developing adaptive AI experiences from inferred preferences.
- Familiarity with implicit preference modeling, consumer decision making, personalized recommendation systems, or user modeling.