Human-Centered AI Intern, AI & Behavior Change at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Automotive, AI Research, SustainabilityIndustries

Requirements

Enrolled in PhD degree program in human-computer interaction, artificial intelligence, or a related field
Demonstrated interest in building systems/applications at the intersection of human-AI interaction and human behavior change
Track record of executing research projects from start to finish
Desire to work on challenging, open-ended research projects
Excellent communication and teamwork skills
Desire to be part of a highly interdisciplinary team, and an understanding of how this will improve your work
Desire to apply research skills and findings to real-world problems
Demonstrated ability to work autonomously while soliciting feedback
Interested in the topic space of carbon neutrality, electrified vehicles, and behavior change

Responsibilities

Scope a research project to align with our core research efforts
Be the primary driver of the technical plan (e.g., study design, model development, systems architecture, analysis plan) with regular feedback from your mentor and teammates
Execute the project using TRI resources
Present the project’s approach and findings in research meetings to the Carbon Neutral Department, the HCAI Division, and TRI, as well as for stakeholders from Toyota business groups

Skills

Machine Learning

Generative AI

Human-Computer Interaction

Behavioral Science

Research

Study Design

Model Development

Systems Architecture

Toyota Research Institute

Research in mobility, safety, and automation

About Toyota Research Institute

Toyota Research Institute focuses on improving mobility through research and development in the automotive and technology sectors. The company works on enhancing safety, automated driving, robotics, materials science, and machine learning. Their products include advanced safety features and automated driving systems that aim to make driving safer and more efficient. Unlike many competitors, TRI emphasizes a research-driven approach, collaborating with various partners and licensing their innovations to enhance Toyota's offerings and maintain a competitive edge. The goal of TRI is to advance mobility solutions that improve quality of life and support the transition to zero-emissions transportation.

Los Altos, CaliforniaHeadquarters

2016Year Founded

$100MTotal Funding

SEEDCompany Stage

Robotics & Automation, Automotive & Transportation, AI & Machine LearningIndustries

201-500Employees

Benefits

Highly competitive benefits package

Robust programs to support the wellbeing, happiness, and health of our people and their families.

401(k) plan including matching and annual profit sharing along with total vacation and holidays totaling 38 days per year.

Subsidized commuter benefits and generous employee and vehicle allowances

2 paid days per year to participate in volunteer activities.

Maternity Leave program with 10 paid weeks plus baby bonding leave and Milk Stork for traveling moms

Baby Bonding Leave–an additional 16 paid weeks–to all new parents, including those who choose to adopt.

Back-up child and adult / elder care programs to help everyone thrive

WellBeats Virtual Fitness Trainer.

Risks

Public skepticism may undermine AI-assisted driving safety initiatives.

Boston Dynamics' high costs could impact TRI's humanoid robot project returns.

Complexity of real-world environments may delay TRI's robot skill deployment.

Differentiation

TRI focuses on AI to enhance human life and mobility.

Partnerships with Boston Dynamics and Stanford showcase TRI's collaborative innovation.

TRI's Driving Sensei concept integrates AI to improve driver skills and engagement.

Upsides

Generative AI allows TRI's robots to learn complex tasks without new coding.

TRI's AI-driven material synthesis could revolutionize EV battery development.

Autonomous tandem drifting collaboration with Stanford pushes vehicle dynamics boundaries.

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