Optimization in Generative Models Intern

Toyota Research Institute

Toyota Research Institute

Cambridge, MA, USA
Posted on Saturday, November 18, 2023
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.
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 algorithms for training and guidance of generative diffusion models, with applications in vehicle design. In particular, we are interested in adapting generative modeling techniques that underpin image generation tools like Stable Diffusion and applying optimization techniques to control outputs based on physical engineering constraints.
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 exciting, 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.

Responsibilities

  • Develop and deploy optimization algorithms for controlling and constraining outputs of generative models
  • Design and implement experiments for evaluating performance of these algorithms
  • Publish basic research related to these tasks

Qualifications

  • Ph.D. or MS candidate in Electrical Engineering, Computer Science, Operations Research, or related field

Bonus Qualifications

  • Experience with vision models
  • Experience with 3D representations
  • Designing and training neural networks
  • Convex optimization
  • Mathematical background in numerical linear algebra
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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