Learning to Automate Surgical Tasks from Demonstration

PGR-P-1859

Key facts

Type of research degree: PhD
Application deadline: Ongoing deadline
Project start date: Thursday 1 October 2026
Country eligibility: International (open to all nationalities, including the UK)
Funding: Non-funded
Supervisors: Dr Duygu Sarikaya
Additional supervisors: Professor Pietro Valdastri (Electronic & Electrical Engineering)
Schools: School of Computer Science, School of Electronic and Electrical Engineering

<h2 class="heading hide-accessible">Summary</h2>

Automating repetitive surgical tasks such as surgical suturing, endoscope control or tissue retraction can increase patient safety, efficiency, precision, and reproducibility in operating theatres as well as optimize operating room use times, and better manage resources. While studies on automating surgical tasks are proposed in the literature, most of these solutions require path-planning and defining environment-specific hand-crafted behaviours based on domain knowledge. Therefore, these approaches fail to scale. Reinforcement learning (RL) approaches, on the other hand, have exhibited high scalability in learning diverse control policies, but typically require extensive data collection to solve a task. Reinforcement Learning from expert demonstrations can narrow down exploration and help to achieve efficient training of models. The topics for this project will focus on: - Developing a reinforcement learning policy to learn how to automate surgical tasks from expert demonstrations - Demonstrating the capabilities of the reinforcement learning model in real- world research platforms (in simulation and/or real set up (Da Vinci® Surgical System The project will allow exploration of different ideas and topics, and a chance to work with collaborators from different disciplines (computer science, robotics, medicine). A good knowledge of fundamental topics in machine learning and deep learning, along with strong coding skills is expected. Experience with advanced deep learning topics, particularly deep reinforcement learning, and familiarity with simulation environments for robotics is preferred.

<h2 class="heading">How to apply</h2>

Formal applications for research degree study should be made online through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University's website</a>. Please state clearly in the Planned Course of Study section that you are applying for PHD Computer Science FT, in the research information section that the research degree you wish to be considered for is Learning to Automate Surgical Tasks from Demonstration as well as <a href="https://eps.leeds.ac.uk/computing/staff/13320/dr-duygu-sarikaya">Dr Duygu Sarikaya</a> as your proposed supervisor and in the finance section, please state clearly the funding that you are applying for, if you are self-funding or externally sponsored. If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below). Applications will be considered on an ongoing basis. Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed. If you are applying for University or School Scholarships for 2026/27 entry, with external sponsorship or you are funding your own study, please ensure you provide your supporting documents at the point you submit your application: <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date including the grading scheme</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul> As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.

<h2 class="heading heading--sm">Entry requirements</h2>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and at least 6.0 in reading, listening and speaking or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<h2 class="heading">Funding on offer</h2>

Self-Funded or externally sponsored students are welcome to apply. Scholarship opportunities open from October 2025 UK – The <a href="https://phd.leeds.ac.uk/funding/138-leeds-doctoral-scholarship-2025-faculty-of-engineering-and-physical-sciences#:~:text=Key%20facts&text=One%20Leeds%20Doctoral%20Scholarship%20is,rata%20for%20part%2Dtime%20study.">Leeds Doctoral Scholarship</a> (closing date: February 2026) and <a href="https://phd.leeds.ac.uk/funding/234-leeds-opportunity-research-scholarship-2022">Leeds Opportunity Research Scholarship</a> (closing date: April 2026) are available to UK applicants. <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds. Non-UK – The <a href="https://phd.leeds.ac.uk/funding/48-china-scholarship-council-university-of-leeds-scholarships-2021">China Scholarship Council - University of Leeds Scholarship</a> is available to nationals of China (closing date: January 2026). The <a href="https://phd.leeds.ac.uk/funding/73-leeds-marshall-scholarship">Leeds Marshall Scholarship</a> is available to support US citizens. <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds. Please note that if you are successful in securing an academic offer for PhD study, this does not mean that you have been successful in securing an offer of funding. If you are applying for the Leeds Doctoral Scholarship, Leeds Opportunity Research Scholarship, China Scholarship Council-University of Leeds Scholarship or Leeds Marshall Scholarship, you will need to complete a separate application, specific to these scholarships, to be considered for funding. You will be responsible for paying the overtime fee in full in your writing up/overtime year (£340 in Session 2025/26), but the scholarship maintenance allowance will continue to be paid for up to 6 months in the final year of award. Important: Please note that that the award does not cover the costs associated with moving to the UK. All such costs (<a href="https://www.leeds.ac.uk/international-visas-immigration/doc/applying-student-visa">visa, Immigration Health Surcharge</a>, flights etc) would have to be met by yourself, or you will need to find an alternative funding source. Please refer to the <a href="https://www.ukcisa.org.uk/">UKCISA</a> website for information regarding Fee Status for Non-UK Nationals.

<h2 class="heading">Contact details</h2>

For further information about this project, please contact Dr Duygu Sarikaya by email to <a href="mailto:D.Sarikaya@leeds.ac.uk">D.Sarikaya@leeds.ac.uk</a> For further information about your application, please contact PGR Admissions by email to <a href="mailto:phd@engineering.leeds.ac.uk">phd@engineering.leeds.ac.uk</a>