Energy & Materials Intern - Probabilistic Programming at Toyota Research Institute

Los Altos, California, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Feb, 26

Salary

65.0

Posted On

21 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Probabilistic Programming, Time-Series Analysis, Structural Causal Modeling, Machine Learning, Python, PyTorch, JAX, Causal Inference, Causal Learning, Chemistry, Material Science

Industry

Research Services

Description

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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. The Team The long-term vision of TRI’s Accelerated Materials Design and Discovery (AMDD) program is to accelerate the development of truly emissions-free mobility. Realizing this vision will require the discovery of new materials and devices for batteries, fuel cells, and more. Our aim at TRI is to merge cutting-edge computational materials modeling, experimental data, artificial intelligence, and automation to significantly accelerate materials research. Our focus is on developing tools and capabilities to enable this acceleration. We collaborate closely with a dozen universities and national labs and colleagues across global Toyota. AMDD seeks to develop and translate the newest technologies into practice, both within Toyota and the open research community more broadly. The Internship We are looking for an intern to contribute to the development and/or benchmarking of our probabilistic programming tools. Together, we will develop tools that provide insight into the design and testing of fuel cells, electrolyzers, or related devices. Your day-to-day may include: probabilistic programming, time-series analysis, structural causal model development, and/or machine learning model development. We welcome you to join a unique team of scientists and engineers where you will constantly learn new skills at the interface of materials science and AI. \n Qualifications Currently enrolled in a doctoral program in computer science, statistics, applied math, machine learning, or a related discipline. Have experience with probabilistic programming or probabilistic machine learning applied to time series modeling. Have experience with standard machine learning tools in Python such as PyTorch, JAX, etc. Bonus: Have experience with structural causal modeling, causal inference, causal learning, and/or experience with chemistry or material science. \n Please add a link to Google Scholar to include a full list of publications when submitting your CV for this position. 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, business or organizational needs, market location, job-related knowledge, skills, and experience. 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. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

Responsibilities

The intern will contribute to the development and benchmarking of probabilistic programming tools. This includes developing tools that provide insight into the design and testing of fuel cells, electrolyzers, or related devices.