Robotics Intern, Dynamics and Simulation

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 paid 12-week internship opportunity for Summer 2025. Please note that this internship will be a hybrid in-office role.

The Department

The mission of TRI Robotics is to invent and prove new robotic capabilities required to enable home robots to solve the challenges faced by an aging society. As part of that mission, we are developing a sophisticated suite of open source robotics software called Drake (https://drake.mit.edu), for use in our internal robotics projects and the wider community of advanced robotics researchers.

The Team

Within TRI Robotics, the Dynamics and Simulation team develops Drake tools to model and simulate mobile robot dynamics, object manipulation, and perception. We emphasize physical accuracy and robust, performant software permitting controller synthesis, learning, analysis, regression testing, and design in simulation that transfers meaningfully to the real world. Features include:

- Physics-based, high-fidelity, high-performance software tools for simulation of robots and vehicles interacting with their environments.

- Multibody dynamics, rigid and soft body computational mechanics.

- A unique hybrid dynamic system abstraction and infrastructure (like Simulink blocks, but differentiable and symbolically analyzable).

- Solvers for dynamic systems (numerical integration of DAEs, time stepping, event handling).

- Computational geometry, rendering, and contact response (emphasizing manipulation).

- Validation of simulation accuracy and verification of software and numerical methods.

This is open source, modern C software, developed using rigorous best practices including extensive unit and validation tests, detailed documentation, and collaborative pre-merge peer review. We encourage publication of novel work in peer-reviewed literature and collaboration with the wider robotics community.

Our team consists of computer scientists and engineers trained at leading academic institutions and innovative companies, with research and practical experience in robotics, computer graphics, computational mechanics, multibody dynamics, numerical methods, and software engineering. We have considerable expertise in all these fields and a lot of software to write, so there is much interesting work to do and plenty of opportunity to extend your knowledge in any of the above areas. 

The Internship

We are looking for an intern to work on a research project that will help us advance the capabilities of our simulation tools. During this internship you will collaborate with other software engineers and research scientists to develop physically-accurate, reliable, and fast models and algorithms that are relevant to the simulation and robotics community. Every day, you will work towards solving difficult modeling, mathematical, and implementation problems with a focus on accuracy of simulation results, and reliability and performance of software. Your challenge will be to distill physical and mathematical phenomena into the clearest possible software model, and make it work! The final goal is to publish in a scientific journal and to implement new capabilities in our open source software, Drake.

• Bachelor's degree in Computer Science or equivalent; advanced degree, physics and engineering background a plus.
• Experience developing numerical methods and scientific software including physics-based simulation.
• Solid grasp in at least some of linear algebra, differential equations, partial differential equations, nonlinear equations, geometry, and related numerical methods.
• Excellent software development skills, preferably in C and/or Python.
• Strong understanding of scientific software accuracy and performance issues and tradeoffs.
• Bonus – deep knowledge and expertise in one or more of the following: hybrid systems, multibody dynamics, numerical integration, discrete and differential computational geometry, contact mechanics, differential-algebraic equations, high performance computing, GPU programming.

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