AI Research Intern – Wellbeing, Communities & Organizations

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 Mission
Within TRI’s Human-Centered AI Division, the Harmonious Communities team aims to understand and improve wellbeing in complex systems such as workplaces, organizations, and communities. Our goal is to develop new ways of measuring, modeling, and shaping wellbeing—leveraging AI to support better outcomes at both individual and collective levels.

The Challenge
Wellbeing in real-world systems is complex, and shaped by interactions across individuals, teams, and environments. Many drivers are difficult to observe, measure, or model, and traditional approaches often fail to capture these dynamics. We are exploring how AI—combined with systems thinking—can help uncover hidden patterns, identify key drivers, and enable the design of interventions or system changes that improve outcomes at scale.

The Team
The Harmonious Communities team is an interdisciplinary group of machine learning researchers, behavioral scientists, and human-computer interaction experts. We work across fields to study how wellbeing emerges, evolves over time, and can be influenced through organizational structures, technologies, and policies. Our work connects fundamental research with real-world impact within Toyota.

The Opportunity
We are looking for a creative and self-driven intern to explore how AI can be used to better understand and improve wellbeing in human systems. This is an open-ended, research-oriented internship where the project will be shaped collaboratively based on your interests and ideas. You will have the opportunity to propose and develop novel approaches, including machine learning, causal learning, natural language processing, or agent-based simulations, to study complex social systems.

Responsibilities :
• Formulate and explore research questions related to wellbeing in organizations and communities.

• Work with real or simulated datasets to uncover patterns, relationships, and insights.

• Develop models, simulations, or analytical tools using AI/ML methods.

• Explore approaches such as causal inference, agent-based modeling, or LLM-based analysis where appropriate.

• Communicate findings through reports, visualizations, or lightweight prototypes.

• Collaborate with an interdisciplinary team and incorporate feedback into your work.

Qualifications:
• Demonstrated experience developing AI/ML tools or systems.

• Proficiency in Python and common data science or machine learning libraries.

• Strong problem-solving skills and ability to work in open-ended, ambiguous settings.

• Interest in applying AI to human-centered, real-world problems.

Bonus Qualifications:
• Experience with causal inference, probabilistic modeling, or time-series analysis.

• Experience with NLP, LLMs, or working with unstructured text data.

• Familiarity with agent-based simulations or complex systems modeling.

• Background or interest in social sciences such as psychology, sociology, or organizational behavior.

• Strong interest in creative, unconventional, or underexplored research directions.

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.

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