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PhD Studentship: A surrogate model for the analysis of blood flow through compliant, size-mismatched arterial anastomoses in reconstructive surgery

University of Plymouth - Mechanical Engineering

Qualification Type: PhD
Location: Devon, Plymouth
Funding for: UK Students, EU Students, International Students
Funding amount: The studentship is supported for 3.5 years and includes Home tuition fees plus a stipend of £20,780 per annum 2025-26 rate
Hours: Full Time
Placed On: 27th February 2025
Closes: 28th March 2025

DoS: Dr Adam Kyte

2nd Supervisor: Dr Daniela Oehring

3rd Supervisor: Dr Vincent Drach

4th Supervisor: Prof Rory Rickard.

Applications are invited for a 3.5-year PhD studentship.

The studentship will start on 1st October 2025.

Project Description

Reconstructive surgery regularly requires the anastomosis (surgical joining) of arteries, often with mismatched diameters.  Catastrophic failure can occur due to thrombosis and/or other pathologies, influenced by factors such as vessel size mismatch ratio, vessel mechanical properties, distal resistance/compliance, applied pressure and anastomotic geometry. The surgeon is therefore faced with a complex set of (often conflicting) decisions to avoid anastomotic failure. 

This study will address the research question: “Can a surrogate model be developed in which results are obtained in real time, to assist the surgical decision-making process in arterial anastomosis in reconstructive surgery?”

A numerical model has been developed to predict relevant flow metrics as a function of the above factors.  It uses a Fluid Structure Interaction (FSI) approach, with a Computational Fluid Dynamics blood flow model coupled to a structural Finite Element model of the vessel walls.  However, model solution typically takes several days on a high-spec PC. The proposed project will develop a surrogate model based on results from the existing FSI model, allowing results to be generated almost instantly on a smartphone. Surrogate models are typically based on data-fitting of results from more computationally expensive models, using techniques such as neural networks.

This highly interdisciplinary project involves numerical modelling, machine learning/AI, high performance computing and medical sciences.  It is unlikely that any applicant will have a background in all these areas but should have experience in some of them, with a curiosity and desire to learn in the others.  Programming/computing skills are of particular importance. 

Eligibility

Applicants should have a first or upper second class honours degree in an appropriate subject and preferably a relevant Masters qualification. Applications from both UK and overseas students are welcome.

The studentship is supported for 3.5 years and includes full Home tuition fees, Bench fee plus a stipend of £20,780 per annum 2025/26 rate.  The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications.  Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates.  The international component of the fee may be waived for outstanding international applicants.

There is no additional funding available to cover NHS Immigration Health Surcharge (IHS) costs, visa costs, flights etc.

NB: The studentship is supported for 3.5 years of the four-year registration period. The subsequent 6 months of registration is a self-funded ‘writing-up’ period.

If you wish to discuss this project further informally, please contact:

Adam Kyte (adam.kyte@plymouth.ac.uk).

To apply for this position please click the Apply button above.

Please clearly state the name of the studentship that you are applying for on your personal statement.

Please see here for a list of supporting documents to upload with your application.

For more information on the admissions process generally, please contact research.degree.admissions@plymouth.ac.uk

The closing date for applications is 12 noon on 28th March 2025.

Shortlisted candidates will be invited for interview shortly thereafter.

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