Research Scientist Intern, Robot Learning & Manipulation (Spring, Summer & Fall 2027) | Master’s & PhD Internship

We are offering spring, summer, and fall 2027 research internships in the Irvine office for master’s and PhD students advancing robotic manipulation.

You will investigate how robots can perform useful physical tasks reliably across diverse objects, environments, and robot platforms. Working closely with researchers and engineers, you will own a focused research project and help translate promising ideas into capabilities that can be tested on hardware and improved through real deployment experience.

Research directions and methods will be shaped by your expertise and the problems we encounter in the field. The goal is to produce original research with measurable impact on what our robots can accomplish.

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  Develop manipulation capabilities that address meaningful physical tasks in real environments.

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  Investigate how skills transfer across objects, tasks, environments, and robot platforms.

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  Address practical challenges such as uncertainty, contact, changing conditions, and failure recovery.

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  Design experiments that measure task success, generalization, and reliability under realistic operating conditions.

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  Integrate and validate research on physical robots, collaborating with engineering teams to address system constraints.

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  Document findings, present results, and contribute to publications or reusable research tools.

• 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.

• First-author publications at venues such as RSS, CoRL, ICRA, IROS, NeurIPS, ICLR, or ICML, or journals such as RA-L, T-RO, or IJRR.

• Significant contributions to open-source robotics or machine learning projects with demonstrated adoption.

• Hands-on experience taking research from an initial idea to reliable operation on physical robots.

• Experience evaluating robotic systems outside controlled laboratory conditions.

• Public research code, datasets, or robot demonstrations showing technical depth and measurable results.

• Experience with robot integration, sensing, control, or data collection infrastructure.