Research Scientist Intern, State Estimation for Dexterous Manipulation

• Design and implement latent space representations for object physical state during robotics manipulation tasks that go beyond fixed parameter sets
• Design and execute controlled experiments to validate the representation: measuring adaptation speed, property decoding fidelity, and downstream control performance against baselines (no object state, explicit physical parameters, raw sensor history)
• Benchmark the latent state representation on practical dexterous manipulation tasks
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
• Showcase the value in simulated or physical demos

• Currently has or is in the process of obtaining a Ph.D. degree in Robotics, Machine Learning, Computer Science, or relevant technical field
• Strong background in representation learning, generative models, or neural implicit representations (e.g., Gaussian splatting, NeRF, structured latent variable models)
• Experience with physics-based estimation, state estimation, or system identification in robotic or dynamical systems (e.g. Bayesian filtering, online adaptation, or meta-learning for system identification)
• Experience with Python and PyTorch
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

• Experience with tactile sensing, force/torque sensors, or robot hand manipulation
• Familiarity with model-based control (MPC), reinforcement learning, or imitation learning for manipulation
• Experience with Bayesian filtering, online adaptation, or meta-learning for system identification
• Experience with experimental design and statistical evaluation of robotic systems
• Experience working and communicating cross functionally in a team environment
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI), or similar
• Intent to return to the degree program after the completion of the internship/co-op

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