- Type of research degree
- Application deadline
- Ongoing deadline
- Country eligibility
- International (open to all nationalities, including the UK)
- Competition funded
- Additional supervisors
- Prof Kanti Mardia
- School of Mathematics
- Research groups/institutes
Objects are everywhere, natural and man-made. Advances in technology have led to the routine collection of geometrical information on objects and the study of their shape is more important than ever. Analytically, shape comprises the geometrical information that remains when location, scale and rotational effects are removed from the description of an object.<br /> <br /> In many settings it is possible to define "landmarks" which can be consistently identified across a set of objects, and developments over the past 30 years have led to the new subject of statistical shape analysis, an extension of multivariate analysis. We have pioneered the development of statistical shape methodology for many medical, biological and computational real examples. More details can be found in Dryden, I.L. and Mardia, K.V. (2016) Statistical Shape Analysis with Applications in R, second edition, Wiley. In dynamic shape analysis the shape of an object changes through time.<br /> <br /> The time scale can range from years, e.g. the growth of a human face between childhood and adulthood, down to seconds, e.g. the formation of human facial expressions such as a smile. Such applications can be viewed as multivariate time series, sometimes with change points. It has some methodological connection with our pioneering contribution to growth assessment through facial LASER scans of children.<br /> <br /> The motivating application for this project comes from the use of craniofacial surgery to correct facial deformities such as a cleft lip. One measure of success for the surgery is the ability of the patient to make "normal-looking" facial expressions, such as smile. At the moment this judgement is made subjectively. Using a 3D motion capture camera system, we have already acquired some dynamic data for the normal human smile.<br /> <br /> The aim of the project is to develop and assess more objective measures to quantify the success of surgery, leading to a high impact contribution. Note that no knowledge of shape analysis is necessary.
<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 <em><strong>PHD Statistics FT</strong></em> and in the research information section that the research degree you wish to be considered for is <em><strong>Dynamic shape modelling in reconstructive surgery</strong></em> as well as <a href="https://physicalsciences.leeds.ac.uk/staff/59/professor-kanti-mardia">Prof Kanti Mardia</a> as your proposed supervisor.</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> </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><strong>Self-Funded or externally sponsored students are welcome to apply.</strong></p> <p><strong>UK </strong>– The <a href="https://phd.leeds.ac.uk/funding/209-leeds-doctoral-scholarships-2022">Leeds Doctoral Scholarships</a>, <a href="https://phd.leeds.ac.uk/funding/198-akroyd-and-brown-scholarship-2022">Akroyd & Brown</a>, <a href="https://phd.leeds.ac.uk/funding/199-frank-parkinson-scholarship-2022">Frank Parkinson</a> and <a href="https://phd.leeds.ac.uk/funding/204-boothman-reynolds-and-smithells-scholarship-2022">Boothman, Reynolds & Smithells</a> Scholarships 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.</p> <p><strong>Non-UK </strong>– 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. 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.</p>
<p>For further information regarding your application, please contact Doctoral College Admissions by email: <a href="mailto:firstname.lastname@example.org">email@example.com</a>, or by telephone: +44 (0)113 343 5057.</p> <p>For further information regarding the project, please contact Professor Kanti Mardia by email: <a href="mailto:K.V.Mardia@leeds.ac.uk">K.V.Mardia@leeds.ac.uk</a></p>
<h3 class="heading heading--sm">Linked research areas</h3>