1.76 Robotics Research Internship, Humanoid Manipulation (Summer 2026) | PhD Internship

FieldAI•Boston, MA

About The Position

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use. We are offering a Summer 2026 internship focused on humanoid manipulation for PhD students interested in advancing embodied intelligence on real robotic systems. As a research intern, you will work at the intersection of robotics research and applied engineering, contributing to manipulation capabilities for humanoid robots that directly support FieldAIâs autonomy and robot learning efforts. You will collaborate closely with Field AI research scientists and engineers to design experiments, develop manipulation systems, and test ideas on real hardware. This internship emphasizes translating research into practical, scalable systems, while also contributing to longer-term efforts around embodiment-agnostic robotics foundation models.

Requirements

Current PhD student in Robotics, Computer Science, Mechanical Engineering, AI/ML, or a closely related field.
Research experience in robotic manipulation, loco-manipulation, or related robotics domains.
Strong foundation in robot kinematics, dynamics, and control.
Proficiency in Python and/or C++, with experience using robotics or ML tooling.
Experience designing experiments and evaluating results on robotic systems (simulation or hardware).
Curiosity, initiative, and a strong interest in embodied intelligence and real-world robotics.

Nice To Haves

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.

Responsibilities

Advance Humanoid Manipulation Research
Design, implement, and evaluate manipulation strategies for humanoid robots across diverse tasks.
Explore loco-manipulation problems that integrate perception, planning, and control.
Contribute to research projects from early ideas through on-robot experimentation.
Build Systems That Bridge Research and Deployment
Translate research concepts into working robotic systems tested on real hardware.
Develop experimental setups and tooling to support data collection and evaluation.
Help ensure manipulation systems are robust, reproducible, and field-relevant.
Contribute to Robotics Foundation Model Development
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.
Collaborate Across Disciplines
Partner with mechanical and electrical engineers on hardware integration and system bring-up.
Work with teleoperators and field teams to refine interfaces and improve manipulation outcomes.
Engage closely with researchers and engineers to align experiments with broader autonomy goals.
Rapidly Iterate and Learn
Prototype quickly, run experiments on hardware, and analyze results rigorously.
Balance exploratory research with concrete deliverables over the course of the internship.
Debug system-level issues spanning software, hardware, and learning.