Human-Machine Interaction Research Intern, Human Interactive Driving at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Automotive, AI Research, Human-Computer InteractionIndustries

Requirements

Currently pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields
Experience designing and running experiments with human subjects
Past cross-functional collaboration with other researchers and engineers to invent and develop interesting research ideas
Passionate about developing and applying human-centered artificial intelligence for social good
Reliable team player who likes to think big, go deeper, care about openness, and deliver with integrity
Experience with machine learning (plus)
Experience with devices to measure physiological signals (plus, e.g., EDA, heart rate)
Experience with eye-tracking devices (plus)

Responsibilities

Conduct user studies to evaluate the effectiveness and responses to different interventions to improve driving safety and performance
Create novel interventions that can be used to help people drive better and safer
Partner with a multidisciplinary team including other research scientists and engineers across Toyota Research Institute
Present results in verbal and written communications, both internally and at top international venues

Skills

Human Subjects Experiments

Machine Learning

Eye-Tracking

EDA

Heart Rate Measurement

Physiological Signals

Human-Computer Interaction

Driving Simulator

Design Thinking

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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