Shear wave elastography (SWE) is a non-invasive imaging modality that can be used to detect chronic kidney disease (CKD) 
by distinguishing the stiffness between healthy and diseased kidneys. Current SWE system estimates the stiffness based on 
the speed of shear wave propagation inside the tissue by assuming the tissue to be linearly elastic. Nevertheless, kidneys 
exhibit a myriad of characteristics that go against the linear elastic assumption. Specifically, kidneys are known to be 
an organ that is highly perfused with blood and urine. The presence of fluid within the kidney can alter the speed at 
which shear waves propagate and if this factor is not accounted for, it may give rise to inaccurate estimation of the 
stiffness and subsequently the detection of CKD. This project aims to elucidate the biomechanics of shear wave propagation 
in a fluid-filled renal tissue using a computational modelling approach. Effects of variation in renal perfusion (i.e. 
pressure, and other potential variables) coupled with the influence of tissue viscoelasticity and renal anisotropy would 
allow for more insight into the tissue biomechanics that would occur during shear wave propagation as CKD progresses.

Requirements: 
* Open to everyone.

* Holds a Bachelor degree with CGPA of at least 3.67 (First class) or equivalent (for PhD)] in Mechanical Engineering or a 
related discipline. Students who are expected to graduate in the near future are also encouraged to apply.

* A good knowledge in computational mechanics is required for this project.

* Demonstrated research experience in the form of journal or conference publications is preferable.

* Strong analytical skills and a solid mathematical background.

* Fundamental knowledge in the areas of computational modelling, transport in biological tissues.

* Demonstrated experience in Ansys and knowledge of programming is preferred.

* Excellent, motivated, and self-driven.

Additional content / links to more information such as past papers by research group:

For more information on the Biomedical Engineering Modelling and Simulation (BEMS) group, please visit: 
https://sites.google.com/view/bemsmonash/home


Please send in your CV and any related documents via email OOI EAN HIN: (ooi.ean.hin@monash.edu)