location: Leeds – the main campus

Work time: 37.5 hours a week

Contract type: A fixed term (starting from 1^street January 2026 until 31^street August 2028 – To complete a limited work specific time)

Are you an ambitious researcher ready to contribute to the digital transformation of health care that patients benefit from by making clinical interventions safer, faster and effective?

The project aims to technical innovations in computer vision and computer graphics (retail, registration, tracking and perception) to enable real -time interaction for surgical planning and decision -making. The project will provide an opportunity to work cooperatively with arithmetic scientists and clinical surgeons who explore new ways to transform research and practice surgery. Our research is generously funded by the Engineering and Physical Science Research Council (EPSRC).

We are looking for a research colleague to join our team and lead research efforts in the actual time and the exact challenges facing it somewhat before surgery. Surgery addresses the ambiguity of vision, blockage and other surgical complications.

A successful candidate will be responsible for developing new ways to counter such challenges and create experiences with analized censorship arm and various sensors to understand the basic principles of fake models. You will be a prominent researcher in the group of Dr. Shayib Ali in the field of medicine and surgery (INTelligence.leeds.ac.uk/aims). You will have the opportunity to cooperate with academics and the other clinical team (a unique martyr, a participating project in the project, the NHS TRUST Hospital at the Leeds Education Hospital) to develop and test developed systems.

The candidate is required to obtain a doctorate (or submit your thesis before the role) in computer science/e -engineering and engineering/robots or closely related discipline. You will have a wide background in coding (for example, Python, C ++) and has some works published in first -class conferences/magazines. The candidate must have previous experience in working in the problems associated with vision and experience in deep learning (preferably Pytorch).

We are open to discuss flexible work arrangements.

To explore the post more or for any inquiries you may have, please call:

Dr. Shaib AliLecturer (Assistant Professor)

Email: ssali@leeds.ac.uk

Please note that this post may be suitable for care under the skilled workers ’visa track, but applicants may first need to qualify for salary concessions. For more information, please visit Skilled workers ’visa page.

For research and academic jobs, we will consider eligibility under the global talent visa. For more information, please visit The government page is applying for a global talent visa.