Efficient Physical AI for Real-World Robotics – Funded PhD Studentship

Overview

Durham University offers a fully funded PhD studentship supported by Intel, focusing on efficient physical AI for real-world robotics. The research addresses the limitations of deploying large models on physical robots by developing capable, efficient, and deployable systems that operate under constraints related to compute, memory, latency, power, and training data. Students are co-supervised by Durham academics and an Intel co-supervisor, with opportunities to conduct independent, problem-driven research in a supportive academic setting.

Who can apply

The studentship is open exclusively to applicants with UK Home fee-status. Candidates must hold a relevant undergraduate or master’s degree in disciplines such as computer science, artificial intelligence, engineering, mathematics, physics, or a related field. Essential qualifications include strong programming skills, an interest in machine learning, computer vision, robotics, embodied AI, foundation models, or autonomous systems, motivation to conduct research and publish findings, and the ability to connect theory with implementation and evaluation. Applicants must also meet Durham University's English language requirements. Experience in robotics, reinforcement learning, foundation or vision-language models, efficient inference, or embedded AI is beneficial but not required.

What you get

The position covers Home tuition fees and provides a tax-free stipend. Successful candidates receive regular supervision, professional training in writing, publication, and presentation, and support to build an independent research profile. Researchers gain access to institutional facilities including the Bede regional supercomputer, a departmental GPU cluster, specialized laboratories, drones, embedded devices, and robotic platforms such as humanoid and quadruped robots, as well as direct contact with industry experts at Intel.

Requirements

Applicants must state their UK Home eligibility in all communications and applications. The application package must include a curriculum vitae, academic transcripts, and supporting documents.

How to apply

Candidates must submit their curriculum vitae, transcripts, and supporting documents via email to Dr Amir Atapour-Abarghouei. Applications are reviewed on a rolling basis until the position is filled.

Key dates

The closing date for applications is 2027-01-19.