Robotics Research, Robot Learning & Manipulation Intern (Spring, Summer, & Fall 2027)

Job description

Job responsibilities

• Develop manipulation capabilities that address meaningful physical tasks in real environments.
• Investigate how skills transfer across objects, tasks, environments, and robot platforms.
• Address practical challenges such as uncertainty, contact, changing conditions, and failure recovery.
• Design experiments that measure task success, generalization, and reliability under realistic operating conditions.
• Integrate and validate research on physical robots, collaborating with engineering teams to address system constraints.
• Document findings, present results, and contribute to publications or reusable research tools.

Job requirements

• Current master’s or PhD enrollment in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, AI/ML, or a closely related field.
• Research experience in robotic manipulation, robot learning, embodied AI, or a related area.
• A strong research or open-source track record, demonstrated through substantive publications, research software, or technically rigorous projects.
• Clear ownership of original research or technical development, including implementation and evaluation.
• Strong foundations in robotics, machine learning, and experimental design.
• Proficiency in Python and/or C++.
• Ability to work independently, communicate findings clearly, and collaborate across research and engineering disciplines.