PhD Studentship in Multimodal AI for Context-Aware Surgical Robotics Imperial College London in United Kingdom

This 3.5-year PhD studentship at Imperial College London offers a unique opportunity to advance the field of surgical robotics by integrating multimodal artificial intelligence for context-aware decision support. Hosted within the Hamlyn Centre for Robotic Surgery and the Department of Surgery and Cancer, and funded by the Multi-Scale Medical Robotics Centre, the project aims to transform the surgical robotic console from a passive instrument into an intelligent, context-aware partner. The research will bridge the gap between isolated robotic tools and the wider clinical environment, leveraging recent advances in multimodal foundation models, real-time perception, and agentic AI.

The successful candidate will work at the intersection of Natural Language Processing (NLP), Computer Vision, and Medical Robotics to develop a data-enabled surgical environment. The project focuses on three pillars: multimodal information extraction (using LLMs, VLMs, and knowledge graphs to parse complex patient health data), context-aware surgical intelligence (developing algorithms for real-time surgical phase recognition and anticipation of information needs), and intelligent information presentation (designing interfaces to deliver relevant data to surgeons without distraction).

Students will benefit from access to world-class facilities, including clinical-grade surgical robots and high-performance computing resources. The studentship includes a dedicated travel budget for presenting research at major international conferences such as CVPR, MICCAI, and ICRA. Collaboration with leading clinicians and researchers from Imperial College NHS hospitals provides hands-on insights into surgical practice and mentorship throughout the research journey. Graduates will be well positioned for academic careers in AI and robotics, as well as research roles in healthcare technology and medical AI companies.

Applicants must hold or expect to obtain a First or Upper-Second Class Honours degree (or equivalent) in Computer Science, Engineering, Maths, or Physics. A Master’s degree in a relevant field is advantageous. Essential technical skills include strong programming in Python, proficiency with deep learning frameworks (PyTorch or TensorFlow), and familiarity with software engineering best practices such as Git version control. Experience with RAG, LLMs, VLMs, and robotics is desirable. Candidates must be able to communicate technical concepts to clinical partners and translate surgical needs into engineering requirements. Applications are open to UK and international candidates, with international applicants required to be eligible for a UK Student Visa. Imperial College PhD entry requirements must be met.

The studentship covers full tuition fees (Home and International) and provides a tax-free stipend of approximately £22,780 per annum for 3.5 years. Applications are reviewed on a rolling basis until a suitable pool of candidates is identified, with an expected review date of 28th February 2026. Early application is strongly advised. To apply, submit your CV and contact details of two referees via the online form. Only outstanding applicants will be contacted, and shortlisted candidates must also apply through the Imperial College online portal.