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 Human-Centered AI, Human Interactive Driving, Energy and Materials, Machine Learning, and Robotics.
This is a Summer 2023 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.
TRI's Optimization team develops novel optimization algorithms and software to enhance all aspects of Toyota's business. Our current focus is on algorithms for automatic vehicle design. In particular, we are interested in adapting generative modeling techniques that underpin image generation tools like DALL-E to design tasks.
About The Internship
We are looking for a motivated intern to pursue new avenues of research consistent with the team's mission. This is an opportunity to apply your knowledge to novel research questions and work towards a publication with professional researchers. The internship will be in our Cambridge office and includes competitive compensation befitting the challenging, but fun, nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply.
- Undertake a well-scoped research project in a relevant area and bring it to publication in an appropriate venue.
- Define project scope and agree on project direction with your mentor.
- Ph.D. Student in related fields - ML/AI, optimization, computer science, mechanical engineering, aerospace engineering, or similar.
- Publication background in relevant venues in the field. Proficient at scientific Python and Linux.
- Experience with distributed computing (AWS, particularly) is a plus.
- Experience working on joint scientific projects.
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TRI provides Equal Employment Opportunity without regard to the 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.