ML for Battery Manufacturing Intern
Los Altos, CA
Energy & Materials – Internships - Summer 2024 /
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 Robotics, Human-Centered AI, Human Interactive Driving, and Energy & Materials.
This is a Summer 2024 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.
Energy and Materials
The Energy and Materials Division at TRI is building tools to accelerate the design and discovery of new materials, fostering a transition to more sustainable mobility. Our research applies AI, data-driven methods, and automation to materials science, and spans the atomic to the device scales. Our projects often involve collaboration with scientists from universities and national labs. Interns will be involved in industrial research on topics of broader interest to the general materials science community, and several previous intern projects have resulted in peer-reviewed publications in journals such as npj Computational Materials and Chemical Science.
The TRI Battery Factory of the Future team works to promote the decarbonization of transportation by improving the quality, safety, and cost of batteries and battery manufacturing. We work directly with Toyota manufacturing plants across the US and Japan. Summer interns can expect to work on bleeding edge problems in applied ML for manufacturing, including visual inspection, root cause analysis, and process optimization. Our group places a heavy emphasis on “learn-by-doing”, so you should expect to do engineering work on practical solutions, not theory. Day-to-day responsibilities include developing data pipelines and ML modeling for manufacturing applications, and may include genchi genbutsu visits to North American manufacturing plants, to work on-site with manufacturing subject matter experts. This is an excellent opportunity for anyone who wants to gain a better understanding of the challenges of putting machine learning to work in practice.
- Currently enrolled in a doctoral program in STEM subjects (materials science, chemistry, applied math, statistics, chemical engineering, computer science, or a related discipline)
- Have experience with Python and machine learning
- Experience with CNNs and image classification a plus
- Time-series analysis and physics-informed machine learning experience a plus
Please add a link to Google Scholar and include a full list of publications when submitting your CV to 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; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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