Develop advanced computer vision algorithms for object recognition, scene understanding, visual SLAM, and 3D perception in real-world robotic environments.
Enhance robotic perception systems supporting navigation, localization, manipulation, and task execution using multimodal sensor data (RGB, depth, LiDAR).
Research and prototype modern AI architectures, including:
State of the Art Visual SLAM and Structure from Motion
Large Language Models (LLMs) for robotics
Generative AI and diffusion models
Neural rendering, radiance fields, and Gaussian splatting
Graph neural networks and self-supervised learning
Deploy and evaluate research at scale, transitioning ideas from prototype to production-ready systems.
Collaborate closely with researchers and engineers across computer vision, robotics, machine learning, and software engineering.
Document and communicate findings through technical reports, internal presentations, and (where appropriate) academic publications.

Currently enrolled in a PhD program in Computer Vision, Robotics, Machine Learning, or a closely related field.
Strong foundation in AI, deep learning, and computer vision.
Hands-on experience with PyTorch (preferred) or TensorFlow.
Proficiency in Python; working knowledge of C++ is a plus.
Experience with robot perception systems (e.g., RGB-D cameras, stereo vision, LiDAR).
Strong analytical and problem-solving skills.
Excellent English communication skills and ability to collaborate in a distributed, multidisciplinary team.
Experience working with large-scale datasets or real-world robotics deployments.
Prior publications in top-tier robotics, CV, or ML venues.
Familiarity with SLAM, visual odometry, or 3D reconstruction pipelines.

Unmatched real-world data: Work with data from 15,000+ robots operating across hundreds of customer sites globally.
Real impact: Your work directly influences production robotic systems used daily in live customer environments.
Research meets reality: Bridge cutting-edge academic research with deployment at scale.
World-class mentorship: Learn from experienced researchers and engineers working at the intersection of AI and robotics.
Career pathways: High-performing interns may be considered for future internships, extended research collaborations, or full-time roles.

PhD Research Intern – AI, Computer Vision

Key skills