Blood flow modelling in complex vascular networks: from cancer diagnosis to treatment planning

Blood is a suspension of cells (e.g. red and white blood cells, platelets) and other subcellular material in a Newtonian fluid (i.e. blood plasma). The complex nature of the fluid leads to important differences in the transport properties of the different blood constituents. This is particularly important at the microvascular scale where the vessel diameter becomes comparable to the size of a red blood cell (the most abundant cell type). Little is known about how these differences evolve when blood flows through complex networks.

A broad range of biomedical applications would benefit from an increased understanding of the physics of blood flow in complex networks. For example, vascular networks in tumours display highly abnormal branching patterns. How these structural abnormalities are related to tumour tissue oxygenation (a validated indicator of radiotherapy treatment effectiveness) is largely unknown. Furthermore, by understanding how the characteristics of a network affect the transport of the different blood constituents, one can design microfluidic devices to separate them. This is currently an important bottleneck in the design of liquid biopsy workflows.

Co-supervisors Bernabeu and Krüger have recently developed an extension to the blood flow simulation platform HemeLB that enables the simulation of blood flow as a suspension of deformable particles. Co-supervisor Kersaudy-Kerhoas brings microfluidic engineering expertise that will enable experimental validation of new findings. The supervisory team has a number of ongoing interdisciplinary collaborations spanning mathematicians, cancer biologists, and biomedical engineers interested in applying this technology. We are currently looking for an ambitious and motivated researcher at the PhD student level to join the team. The successful candidate will have the freedom to define her/his own project in the context of these ongoing collaborations.

Supervisors:
• Dr Miguel O. Bernabeu, University of Edinburgh.
• Dr Timm Krüger, University of Edinburgh.
• Dr Maïwenn Kersaudy-Kerhoas, Heriot-Watt University.

Requirements

A strong academic track record with a 2:1 or higher in a relevant undergraduate degree, or its equivalent if outside the UK. A strong performance in a relevant postgraduate degree is desirable. Proven experience in one or more of the following is desirable: mathematical modelling, computational fluid dynamics, image processing or competence in one scientific programming language (e.g. C++, Python, Fortran). The successful candidate will work in a highly interdisciplinary environment and should be able to work independently and as part of a distributed international team.

Following interview, the selected candidate will need to apply and be accepted for a place on the Usher Institute Medical Informatics PhD programme. Details can be found here: https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=924

Application procedure

Please provide a CV, a personal statement detailing your research interests and reasons for applying, degree certificate(s), marks for your degree(s) and two written academic references. All documents should be sent in PDF format to: [Email Address Removed]

For further information about the project contact the primary supervisor: [Email Address Removed]

The closing date for applications is 17 October 2018

Interviews will be held during the week of 22 October 2018.

The studentship will ideally begin in December 2018.