Efficient Physical AI for Real-World Robotics PhD

Durham University invites applications for a fully funded PhD studentship focusing on efficient Physical AI and real-world robotics, co-supervised by academic experts and Intel engineers. The research addresses core limitations in deploying foundation models and machine learning on hardware constrained by power, memory, and compute. The successful candidate will design novel algorithms, evaluate robot foundation models, and conduct experiments using state-of-the-art robotic platforms. Applicants are expected to pursue independent, problem-driven research and contribute to academic publications.

• Design and implement efficient machine learning and computer vision algorithms for robotic deployment
• Investigate foundation models, vision-language-action models, and reasoning frameworks for real-time tasks
• Conduct experimental evaluations using physical robot platforms, including humanoids, quadrupeds, and aerial vehicles
• Bridge the gap between simulation environments and real-world physical deployment
• Collaborate closely with industrial partners at Intel on edge AI and compact model optimization
• Prepare research findings for publication in top-tier academic venues and present results at conferences