Durham University
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PhD Studentship in Efficient Long-Horizon Task Execution in Physical AI (Deep Learning, Computer Vision, Robotics) Durham University in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Aug 15, 2026
Country
United Kingdom
University
Durham University

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About this position
Durham University is offering a fully funded PhD studentship in Efficient Long-Horizon Task Execution in Physical AI, with a research focus spanning deep learning, computer vision, robotics, embodied AI, edge AI, and intelligent autonomous systems.
The project investigates how robots can reason, plan, act, recover from failures, and replan over long task horizons while remaining efficient enough for real-world deployment. Possible research directions include long-horizon planning with monitoring and recovery, hybrid reasoning, vision-language task decomposition, world models for prediction and planning, reactive-deliberative architectures, compute-aware evaluation, edge/cloud orchestration, and real-robot testing.
The studentship is delivered in collaboration with Intel, including industrial co-supervision, and the student will work with Durham University academic supervisors and an Intel co-supervisor. The post highlights access to strong research infrastructure, including Bede HPC, GPU clusters, LiDAR, RADAR, drones, cameras, embedded devices, and robots such as humanoids, quadrupeds, UGVs, and aerial platforms.
Supervision: Dr Amir Atapour-Abarghouei, Prof Toby Breckon, and Dr Samet Akcay (Intel Principal Engineer, Edge Computing).
Eligibility: Applicants should have a relevant undergraduate or master’s degree in computer science, AI, engineering, mathematics, physics, or a related field; strong programming skills; interest in ML, computer vision, robotics, embodied AI, or autonomous systems; and the ability to conduct independent research. Durham English language requirements apply. Experience in robotics, reinforcement learning, foundation/vision-language models, or efficient inference is desirable but not essential. This opportunity is for Home fee-status applicants only.
Funding: Home tuition fees are covered and a tax-free stipend is provided.
Deadline: 15 August 2026. Applications are expected to be submitted by email, with interviews following shortly after for a proposed October 2026 start date.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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