The project aims to develop novel methods for shape representation and optimization. Shape representation is a critical element that affects the outcome of a shape optimization exercise. Little flexibility leads to constrained family of designs while ones with too many variables can be difficult to optimize. The resulting functional landscape can also be different with different levels of non-linearity.
This research aims to develop novel methods for shape representation and optimization.
Required Background: Good programming in Python and analytical skills, preferably with a Masters Degree in Engineering / Computer Science. Prior research experience in optimization is desirable but not necessary. Demonstrated competence in academic writing and oral presentation skills will be beneficial.
More information: You can find more details of the research conducted in our Multidisciplinary Design Optimization (MDO) group. Please feel free to reach out and discuss regarding this project, or have a discussion about other potential topics for undertaking Masters (research) or PhD with us.
How to Apply
Express your interest in this project by emailing Professor Tapabrata Ray at t.ray@adfa.edu.au. Include a copy of your CV and your academic transcript(s).
School / Research Area
Engineering and IT, UNSW Canberra
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