PhD Studentship: Predictive Network Intelligence for Medical Telerobotics

University of Warwick –Collaborative EPSRC Doctoral Landscape Award.

Qualification: Doctor of Philosophy in Engineering (PhD)

Eligibility: UK Students

Award value: Tuition fees and tax-free stipend - See advert for details

Deadline: 13 April 2026

Supervisors: Dr Zhenhui Yuan and Professor Joseph Hardwicke

Predictive Network Intelligence for Medical Telerobotics

Research area and project description:

Imagine a surgeon operating remotely through a robot—what if the network slows at a critical moment? Even tiny delays can risk patient safety. This PhD project develops new AI approaches to predict network conditions in advance, enabling the robot to adapt and protect the patient. Working closely with clinical experts at University Hospitals Coventry and Warwickshire/NHS Trust, this research will combine robotics, AI, and next-generation networks to make remote surgery safer.

Robotic-assisted surgery is becoming increasingly common in modern healthcare, enabling greater precision, smaller incisions, and faster patient recovery. In the UK, the number of robotic-assisted procedures has increased by 626% from 2017 to 2024, with over 100,000 procedures performed in 2024 alone, and continued rapid growth is expected. Advances in communication networks, particularly 5G and future 6G, now enable telerobotic surgery, allowing surgeons to operate remotely.

However, communication delay remains a critical challenge, as even small delays can affect robot responsiveness and create safety risks. This issue is exacerbated by the fact that the modern Internet infrastructure was originally designed to provide best-effort services rather than guaranteed real-time performance, and the transmission of multi-modal data streams in telesurgery—such as point clouds, haptic feedback, and audiovisual signals—places additional strain on bandwidth, latency, and reliability requirements. This project addresses this challenge by designing an intelligent approach that predict network conditions in advance and provide early warning and adaptive control to ensure safe and reliable human–robot interaction.

The PhD project will develop AI-empowered predictive models that anticipate network delay and instability using historical and real-time data. These models will enable robotic systems to warn the surgeon, adapt control sensitivity, or restrict delicate actions when network conditions degrade. The research will focus on basic laparoscopic surgery tasks, using data collected under varying network conditions and applying machine learning and time-series modelling to predict delay. The models will be integrated into a real-world robotic test platform and evaluated in realistic scenarios to assess improvements in safety and performance.

Scholarship:

The award will cover the UK tuition fee level, plus a tax-free stipend, currently £21,805, paid at the prevailing UKRI rate for 3.5 years of full-time study. The award also includes a £5,000 research training support grant.

Eligibility:

Home students are eligible to apply. The candidate should have a good 2.1 Bachelors, or Masters degree in Electronic Engineering, Computer Sciences or equivalent.

Experience in communications and networking, AI, or robotics is desirable but not essential.

How to apply:

Candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area by clicking the 'Apply' button above. If this initial application is successful, we will invite you to submit a formal application.

Candidates must fulfil the University of Warwick entry criteria and obtain an unconditional offer before commencing enrolment.

Should your application for admission be accepted, you should be aware that notification of acceptance for the PhD does not constitute an offer of financial support. Successful scholarship candidates will receive an official communication to confirm their award.

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