Research Fellow in High-Fidelity Augmented Reality in Laparoscopic Liver Resection

Location: Leeds - Main Campus

Working time: 37.5 hours per week

Contract type: Fixed term (Starting from 1^st January 2026 until 31^st August 2028 - to complete specific time limited work)

Are you an aspiring researcher willing to contribute towards digital transformation of healthcare benefitting patients by making the clinical interventions safer, faster and effective?

The project is aimed at technical innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision making. The project will provide an opportunity to collaboratively work with computational scientists and clinical surgeons exploring novel ways to transform research and practice in surgical care. Our research is generously funded by the Engineering and Physical Sciences Research Council (EPSRC). 

We are seeking a Research Fellow to join our team and lead the research efforts in real-time and highly accurate preoperative-to-intraoperative fusion challenges in surgery tackling vision ambiguity and occlusions and other surgical complications. 

The successful candidate will be responsible for developing novel ways to tackle such challenges and in setting up experiments with controlled robotic arm and various sensors for understanding the underlying principles on phantom models. You will be a leading researcher in Dr Sharib Ali’s AI in Medicine and Surgery group (artificial-intelligence.leeds.ac.uk/aims). You will have the opportunity to collaborate with other academics and clinical team (Shahid Farid, project co-lead, Leeds Teaching Hospital NHS Trust) to develop, and test developed systems.

The candidate is required to hold a PhD (or have submitted your thesis before taking up the role) in computer science/Electronic and Electrical Engineering/Robotics or a closely related discipline. You will have an extensive background in coding (e.g., python, C++) and have some works published in top-tier conferences/journals. Candidate must have prior work experience in vision related problems and experience in deep learning (preferably using PyTorch). 

We are open to discussing flexible working arrangements.

To explore the post further or for any queries you may have, please contact: 

Dr Sharib Ali, Lecturer (Assistant Professor)

Email: S.S.Ali@leeds.ac.uk

Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information, please visit the Government’s Skilled Worker visa page.

For research and academic posts, we will consider eligibility under the Global Talent visa. For more information, please visit the Government’s page, Apply for the Global Talent visa.

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