Postdoctoral Researcher, Human Aware Interaction Learning

Toyota Research Institute (TRI) is looking for a motivated and capable postdoc to conduct research on the computational and machine learning aspects of human-robot interaction, with an emphasis on applying foundation models to human-robot collaboration. The fellowship is based in the Cambridge, MA research center and aims to develop AI approaches that challenge traditional approaches to novel interactions with a human collaborator and enable new embodied interactive policies, with publications in top-tier conferences.

Responsibilities

Perform research and publish on relevant topics in appropriate venues (e.g., ICRA, CVPR, NeurIPS, HRI); Focus publications on how novel representations allow robots to learn to interact with humans towards long-term shared autonomy in a data-efficient, robust, and explainable way; Explore computational and cognitive phenomena, working with a team of researchers to create new approaches for understanding, predicting, and interacting with humans; Work from approach inception and ideation to validation of the developed approaches

Requirements

Ph.D in related fields (by end date) in ML/AI, robotics, human-centric AI, or computer vision; Some experience with robot systems is needed; Strong publications record in top ML/robotics venues, specifically in robot foundation models and their use for human interaction, ML and synthetic data for human-collaborative embodied reasoning, imitation/reinforcement learning, and learning-based shared control and planning for human interactions; Coding in Python, with experience working in a team on joint scientific projects; Experience training deep learning models in e.g., PyTorch/TensorFlow; Ability to refine a topic and execute a scientific research plan in collaboration with other researchers

Nice to have

Relevant background in robot foundation models (e.g., VLAs, WAMs); Imitation/reinforcement learning; Leveraging language conditioning in trajectory planning/prediction; Decision-making under uncertainty; Human-machine teaming/shared control; Relevant publications in these fields

Benefits

Medical, dental, and vision insurance; 401(k) eligibility; Paid time off benefits (including vacation, sick time, and parental leave); Annual cash bonus structure