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Job Record #16824
TitlePore-scale modelling of drug transport in tumour tissue
CategoryPhD Studentship
EmployerUniversity of Aberdeen
LocationUnited Kingdom, Aberdeen
InternationalYes, international applications are welcome
Closure DateTuesday, January 05, 2021
Pore-scale modelling of drug transport in brain tumour tissue

About the Project
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 as soon as possible, for a period of 
three years.


Formal applications can be completed online:

• 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 

Informal enquiries can be made to Dr W Zhan ( with a copy of 
your curriculum vitae and cover letter.

Funding Notes
The award is primarily available to UK/EU students and will pay full tuition 
fees and a maintenance grant (£15,285 pa - tax free - in 2020/2021). We are 
willing to accept applications from international applicants providing they 
are aware that they will have to pay the difference between the UK/Home 
Tuition Fees which will be approx. £16,600 per annum.
Contact Information:
Please mention the CFD Jobs Database, record #16824 when responding to this ad.
NameWenbo Zhan
Email ApplicationNo
Record Data:
Last Modified23:38:06, Tuesday, November 03, 2020

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