Malignant glioma is characterised as aggressive and invasive in clinic owing to its high mortality rate. The efficacy of chemotherapy remains disappointing, limited by the drug heterogeneous distribution that is determined by complex interplays between the intrinsic properties of tumour and biophysical aspects of drug transport. One of the central challenges in chemotherapy is to improve drug transport in tumour tissue for deep penetration and homogeneous distribution.
Drugs transport in tumour extracellular space after crossing the blood vessel wall. This space moulds a web of gaps that is filled with cerebrospinal fluid. How drugs transport in this complex structure remains unclear. Knowledge of the transport mechanisms will allow enhancing the drug penetration, and thereby improve survival by contributing to a more effective therapy that will consequently enhance patients’ life quality.
This fully-funded PhD project is to investigate drug transport mechanisms in brain tumour extracellular space by means of image-based pore-scale modelling, with the aim to identify practical approaches to improve drug distribution. It will be built on a recently developed pore-scale modelling framework to extend the predictive capacity for simulating cerebrospinal fluid flow and drug particle transport. Collaborations with researchers in Medicine will be essential for the collection of microscopic images of tumour tissue.
Based on the skills available in the research team, this PhD project will be supported in different aspects including drug transport model, flow in porous media, medical image processing and pore-scale modelling. Successful completion of this interdisciplinary project will equip the candidate with skills including analysing biological phenomena using engineering principles, computational fluid dynamics and coding, microscopy, image processing, scientific writing and presentation skills, and project management.
Selection will be made on the basis of academic merit. The successful candidate should have, or expect to obtain, a UK Honours degree at 2.1 or above (or equivalent) in Mechanical / Chemical / Biomedical Engineering or a related field. With essential knowledge of fluid mechanics, mass transfer and computational fluid dynamics. Knowledge of Lattice Boltzmann method, discrete element method and microscopic image processing would be desirable.
This is a full-time position, starting in October 2020, for a period of three years.
Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php
• Apply for the Degree of Doctor of Philosophy in Engineering
• State the name of the lead supervisor as the Name of Proposed Supervisor
• State the exact project title on the application form
Applications should include:
1. Degree certificates and grade transcripts (in original language and officially translated into English)
2. A motivation letter / research statement
3. Two academic reference letters
4. Links to publications, if any
5. Detailed CV
If a suitable candidate is found before the closing date the advert will be removed.
Informal enquiries can be made to Dr W Zhan ([email protected]
) with a copy of your curriculum vitae and cover letter.