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Learning to Automate Surgical Tasks from Demonstration

PGR-P-1859

Key facts

Type of research degree
PhD
Application deadline
Monday 31 May 2027
Project start date
Friday 1 October 2027
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.<br /> <br /> The topics for this project will focus on:<br /> *Developing a reinforcement learning policy to learn how to automate surgical <br /> tasks from expert demonstrations<br /> *Demonstrating the capabilities of the reinforcement learning model in real- <br /> world research platforms (in simulation and/or real set up (Da Vinci® Surgical <br /> System <br /> <br /> The project will allow exploration of different ideas and topics, and a chance to work with collaborators from different disciplines (computer science, robotics, medicine).<br /> <br /> 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>

<p>To apply for this project you will need to make a formal application for research degree study through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University website</a>. You will need to create a login ID with a username and PIN. </p> <p>•    For <strong>Application type</strong> please select <strong>Research Degrees – Research Postgraduate</strong>. <br /> •    The admission year for this project is <strong>2027/28</strong> Academic Year. <br /> •    You will need to select your <strong>Planned Course of Study</strong> from a drop-down menu. For this project, scroll down and select <strong>PHP Computer Science Full Time.</strong> <br /> •    The project start date for this project is <strong>1 October 2027</strong>, please use this as your <strong>Proposed Start Date of Research</strong>. <br /> •    Please state clearly in the<strong> Research Information Section</strong> that the research degree you wish to be considered for is <strong>Learning to Automate Surgical Tasks from Demonstration</strong> as well as <a href="https://eps.leeds.ac.uk/computing/staff/13320/dr-duygu-sarikaya">Dr Duygu Sarikaya</a> as your proposed supervisor.</p> <p><strong>Please state clearly in the Finance section</strong>, <strong>the funding that you are applying for, if you are self-funding or externally sponsored</strong>.</p> <p>More information on how to apply is available on our website <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">here</a>. You will be required to provide a personal statement which outlines your interest in the project you are applying for, why you have chosen it and how your skills map onto the requirements of the project.</p> <p>We will assess applications continuously as we receive them. We welcome and strongly encourage any potential applicants to contact the supervisor(s) for an informal discussion, prior to applying, and recommend submitting your application early.</p> <p><strong>If you are applying with external sponsorship or you are funding your own study, please ensure you provide your supporting documents at the point you submit your application:</strong></p> <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> <p>If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below).</p> <p><em>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.</em></p>

<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>

<p>This is a non funded PhD project. Applicants are expected to be self funded or to secure external funding.</p> <p>You can find out more about our Funding Opportunities on our <a href="https://phd.leeds.ac.uk/">Postgraduate Research Opportunities</a> website.</p> <p><strong>Important: </strong>Please note that all costs associated with your arrival at Leeds (<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.</p>

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

<p style="margin-bottom:11px">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></p> <p>For further information about your application, including how to apply, please contact PGR Admissions by email to <a href="mailto:epspgradmissions@leeds.ac.uk">epspgradmissions@leeds.ac.uk</a></p>