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PhD Research Internship in Physical AI Perception

ZooxFoster City, CA
On-site Internship

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Experience Level

Entry Level

Qualifications

Currently enrolled in a PhD program in Computer Science, Artificial Intelligence, or a related field. Strong background in computer vision and machine learning. Familiarity with vision-language-action integration and spatial reasoning techniques. Proficient in programming languages such as Python, C++, or similar. Able to demonstrate strong analytical skills and a passion for innovative research. Excellent communication and collaborative skills.

About the job

About Zoox

Zoox designs and builds fully autonomous electric vehicles, aiming for a future where transportation is safer, more sustainable, and accessible. The team values innovation, collaboration, and a forward-thinking approach to mobility.

Internship Program Overview

Zoox’s internship program offers hands-on experience with advanced technology and mentorship from experienced professionals in the field. The program looks for PhD interns with strong academic records, curiosity, and a commitment to Zoox’s mission. Engagement in activities beyond coursework is also valued.

About the Physical AI Perception Internship

This research internship sits within the Perception Semantics team, which focuses on developing AI systems that help robots interpret and interact with the physical world. Interns will explore topics in vision-language-action (VLA) modeling, world modeling, spatial reasoning, and mapping. The work spans both theoretical research and practical implementation.

Projects are exploratory and research-driven, encouraging interns to investigate new ideas, create solutions, and test them in real-world scenarios. This role suits PhD candidates interested in pushing the boundaries of computer vision and embodied AI, with the opportunity to see their research have real impact.

About Zoox

Zoox is at the forefront of revolutionizing transportation with autonomous electric vehicles, designed for a future where driving is a thing of the past. Our mission is to create a safer, more sustainable, and universally accessible transport system.

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