PhD in machine learning based robotic visual servoing with real-time cardiac calcification imaging

This project will develop and validate a miniaturised intracardiac robotic visual-servoing system based on photoacoustic imaging . The system will support real-time tissue calcification characterisation and lipid-specific plaque mapping during routine cardiac catheterisation procedures, enabling safter, more reliable automatic navigation. This advance in miniaturised robotic vision could influence minimally invasive imaging across multiple medical specialties. The research will generate new knowledge about photoacoustic tissue interactions in calcified cardiovascular tissues and establish methods for multimodal cardiovascular imaging for robotic surgery.<br /> <br /> An inclusive environment and supportive application process: 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.<br /> <br /> Interested? Discuss this PhD Opportunity with Dr Shufan Yang by contacting: s.f.yang@leeds.ac.uk<br />

<p style="margin-top:7px; margin-bottom:13px"><strong>Background:</strong></p> <p>The integration of photoacoustic vision technology into existing robotic catheterisation workflows represents a significant advancement in point-of-care cardiovascular imaging. The PhD programme will provide comprehensive training in cutting-edge biomedical engineering technologies, including machine learning driven vision photoacoustic imaging physics, ultrasound transducer design, laser optics, and biomedical signal processing.</p> <p><strong>Research objectives:</strong></p> <p>Develop and validate a real-time, intracardiac photoacoustic (PA) and ultrasound (US) system, powered by machine learning, to detect and visualise tissue calcification at the catheter–tissue interface,  improving the safety and efficiency of catheter-based cardiac procedures.</p> <p><strong>Training and Career Development</strong></p> <p>You will gain interdisciplinary skills in machine learning, medical image analysis, and photoacoustic imaging. By contributing to accessible cardiovascular diagnostic technologies, you will build practical experience at the intersection of AI-driven healthcare innovation and clinical application.</p> <p><strong>Skills Required</strong></p> <p>Candidates should hold a good bachelor’s degree (first or upper second-class honours degree) or an MEng/MSc degree in a relevant engineering/science subject.</p> <p><strong>Research Environment</strong></p> <p>You will join the multi-disciplinary, dynamic Institute of Medical and Biological Engineering (iMBE) embedded within the School of Mechanical Engineering and the Faculty of Biological Sciences at the University of Leeds. The IMBE is a world-renowned medical engineering research centre which specialises in research and translation of medical technologies that promote ’50 active years after 50’.</p> <p>As a PhD student within IMBE, there will be opportunities to contribute to wider activities related to medical technologies including public and patient engagement, group training and social events. Groups of researchers working on aligned projects or using similar methods meet regularly to share ideas and best practice, and we encourage collegiate working. We will support your long-term career ambitions through bespoke training and encourage external secondments, laboratory visits or participation at international conferences.</p> <p><strong>Our Commitment to an Inclusive, Equitable and Diverse Research Community:</strong> As an international research-intensive university, we welcome students from all walks of life and from across the world. 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.</p> <p>We can help support your application! – Contact our <a href="https://contextualoutreach.leeds.ac.uk/pgr-diversity/access-to-research/">Access to Research team</a></p>

<p>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 <strong><em>EPSRC DTP Engineering & Physical Science</em>s </strong>and in the research information section that the research degree you wish to be considered for is <strong><em>PhD in machine learning based robotic visual servoing with real-time cardiac calcification imaging</em> </strong>as well as <a href="https://eps.leeds.ac.uk/mechanical-engineering/staff/14212/dr-shufan-yang">Dr Shufan Yang</a> as your proposed supervisor.  <em><strong>Please state in the Finance section that you are applying for the EPSRC Doctoral Landscape Award 2026/27: Mechanical Engineering.</strong></em></p> <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>Applications will be considered after the closing date. 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.</p> <p>Please note that you must provide the following documents in support of your application by the closing date of Friday 14 November 2025:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date including grading scheme</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul> <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>

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.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, 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.

<p>A highly competitive EPSRC Doctoral Landscape Award providing full academic fees, together with a tax-free maintenance grant at the standard UKRI rate (£20,780 in academic session 2025/26) for 3.5 years.  Training and support will also be provided.</p> <p>This opportunity is open to UK applicants only.  All candidates will be placed into the EPSRC Doctoral Landscape Award Competition and selection is based on academic merit.</p> <p>Please note that there is only 2 funded place(s) available and there are 17 projects in competition for this funding.  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.</p> <p>Please refer to the <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.ukcisa.org.uk%2F&data=05%7C02%7CJ.S.Hewer%40leeds.ac.uk%7C07632c93c06a442dca3d08ddfc172939%7Cbdeaeda8c81d45ce863e5232a535b7cb%7C0%7C0%7C638943898649349324%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=nylGSov8jOc7hr6X%2FmfnfQPecbVUnGqgoSqVgPGy5K0%3D&reserved=0">UKCISA</a> website for information regarding Fee Status for Non-UK Nationals</p>

<p>For further information about this project, please contact Dr Shufan Yang by email to <a href="mailto:S.F.Yang@leeds.ac.uk">S.F.Yang@leeds.ac.uk</a></p> <p>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></p>