Robotics Research Internship, Humanoid Manipulation (Spring 2027) | PhD Internship

Design, implement, and evaluate manipulation strategies for humanoid robots across diverse tasks.

Explore loco-manipulation problems that integrate perception, planning, and control.

Work towards super-human dexterity, developing systems that outperform human teleoperation.

Work towards publishing a paper in a leading robotics conference/journal

Work closely with other researchers, both internal and external.

Present your work at Field at robotic conferences

Support data collection pipelines used to train robotics foundation models.

Work with embodiment-agnostic representations to enable transfer across robot platforms.

Collaborate with researchers to integrate manipulation data into scalable learning frameworks.

Work with teleoperators and field teams to refine interfaces and improve manipulation outcomes.

Partner closely with researchers and engineers to align experiments with broader autonomy goals.

Engage with mechanical and electrical engineers on hardware integration and system bring-up.

Prior experience working with humanoid robots or dexterous robotic hands.

Background in learning-based manipulation, including imitation learning or reinforcement learning.

Hands-on experience running experiments on real robot hardware.

Familiarity with ROS or ROS 2.

Publications, preprints, or open-source contributions in robotics or AI.

Interest in bridging cutting-edge research with practical, field-ready robotic systems.