Energy & Materials Intern - Probabilistic Programming at Toyota Research Institute

Los Altos, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Energy, Materials Science, Automotive ResearchIndustries

Requirements

Currently enrolled in a doctoral program in computer science, statistics, applied math, machine learning, or a related discipline
Experience with probabilistic programming or probabilistic machine learning applied to time series modeling
Experience with standard machine learning tools in Python such as PyTorch, JAX, etc

Responsibilities

Contribute to the development and/or benchmarking of probabilistic programming tools
Develop tools that provide insight into the design and testing of fuel cells, electrolyzers, or related devices
Perform probabilistic programming, time-series analysis, structural causal model development, and/or machine learning model development

Skills

Key technologies and capabilities for this role

probabilistic programmingprobabilistic machine learningtime-series analysisstructural causal modelsmachine learningcomputational materials modelingAI

Questions & Answers

Common questions about this position

What is the pay range for this internship?

The pay range is expected to be between $45 and $65 per hour for California-based roles, depending on factors like skills, experience, and location.

What benefits are offered for this position?

TRI offers a generous benefits package including medical, dental, and vision insurance, as well as paid time off benefits including holiday pay and sick time.

Is this internship remote or location-based?

This information is not specified in the job description.

What skills are required for this internship?

Candidates must be currently enrolled in a doctoral program in computer science, statistics, applied math, machine learning, or related field, with experience in probabilistic programming or probabilistic machine learning applied to time series modeling, and standard ML tools in Python like PyTorch or JAX.

What should I include in my application for this role?

Include a link to your Google Scholar profile with a full list of publications when submitting your CV.

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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