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PhD vacancy at Deakin University with Dr Alban Vaucorbeil on the Material Point Method

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Dr. Alban de Vaucorbeil from Deakin University (Victoria, Australia) has a tax-free PhD Scholarship available from November 2023. Funding to conduct research and stipend is provided. The student will be located in Geelong, Australia, close to the city of Melbourne and the famous Bells Beach, Torquay.

Research Topic

The Material Point Method is a hybrid meshfree numerical method which is commonly used to solve challenging large deformation solid/fluids mechanics problems. In this method, we have a background grid, which is fixed, and a set of particles moving freely over this grid. These particles carry the state of the solid: stresses, strains, temperatures, volume etc. Mathematically, the Material Point Method is a numerical method to solve partial differential equations encountered in solid mechanics (linear momentum equations).

Although it has been used to solve many problems, the method suffers from some fundamental problems. They are:

1. Energy conservation loss.

2. Poor accuracy in solving contact problems (for example, the penetration issue).

3. High computational cost.

This research is in partnership with Dr Phu Nguyen at Department of Civil Engineering, Monash University.

Project Aim

The project aims at developing techniques to mitigate some of the above mentioned issues. Specifically, the student needs to

  1.  investigate the source of the issues,
  2. develop algorithms/methods to solve them,
  3. implement in an in-house Material Point Method code and
  4. testing the performance of the implemented algorithms.

Eligibility criteria

  1. ‘Applicants must meet Deakin's PhD entry requirements, be enrolling full time and hold an Honours degree (First Class) or an equivalent standard Master's degree with a substantial research component. Please refer to the entry pathways to higher degrees by research for further information.’
  2. Applicants with an engineering, or physics, or applied mathematics or computer sciences background are welcome to apply.
  3. Strong coding experience is required, either in Python, C++ or Julia.
  4. Numerical analysis (partial differential equations), linear algebra skills are required
  5.  Linux/Unix knowledge is preferable.

How to Apply

The student should contact Dr Alban de Vaucorbeil (


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