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 Energy & Materials, Human-Centered AI, Human Interactive Driving, and Robotics.
This is a summer 2025 paid 12-week internship opportunity with the HID Optimization team at TRI. Please note that this internship will be a hybrid in-office role based in Cambridge, MA.
The Team
TRI's Optimization team develops novel optimization algorithms and software to enhance all aspects of Toyota's business. Our current focus is on the interplay between optimization algorithms and diffusion models. In particular, we are interested in adapting diffusion to constrained optimization problems arising in engineering design and automatic control.
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. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply.

Responsibilities

• Define project scope and agree on project direction with your mentor
• Undertake a well-scoped research project in a relevant area and bring it to publication in an appropriate venue
• Have a high level of self-initiative to prioritize and manage workload and meet project deadlines in a dynamic environment
• Work and collaborate with other stakeholders and HID team members

Qualifications

• Currently pursuing a Ph.D. student in related fields - ML/AI, optimization, computer science,  applied mathematics, or similar
• Publication background in relevant venues (e.g. NeurIPS, ICML, ICLR, SIOPT, Math Programming)
• Proficient at Linux, PyTorch
• Strong written and oral communication skills
• Experience with distributed computing (e.g. AWS) a plus

Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.
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