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PhD at UNSW, Sydney – Towards personalised coronary artery disease consideration with Image segmentation, Computational Modelling and machine learning?

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

This project is highly interdisciplinary, and will involve working with (and extending) a suite of existing software and computational models based on clinical imaging data.

Responsibilities evolve around medical image segmentation and processing from dicom images using VMTK and similar tools, use of machine learning algorithms, bash programming and meshing programs to run computational simulations and data post-processing in python, MATLAB and R on a cluster.

Strong problem-solving skills are required and the interest in and willingness to learn about cardiovascular physiology is important.

This position is suitable for students from computer sciences, mechanical/ biomedical/electrical engineering or bioinformatics. Previous research experience is highly desired.

Applicants must have:
- a GPA higher than 3.6/4.0, 90 (for international students), or WAM >80 for Australian residents, and
- must come from a top 200 University for their under- and postgraduate study (QS, times or shanghai ranking), and
- have at least one ISI journal paper in the Q1 tier, and
- meet the UNSW English language requirements, and
- intend on enrolling as a full-time HDR candidate in the commencing semester after successful application.

Students with a home country sponsored scholarship are welcome.

Please apply with your CV, references and cover letter addressing all the selecting criteria.

Funding Notes

Candidates who are invited to apply by Susann, will enter the UNSW scholarship application round with their PhD application. Enrollment typically takes place in the semester after the successful outcome.


Two recent academic referee contacts must be provided with each expression of interest.

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