TUO
Deep learning for cardiac medical image analysis
✓ Funded (Competition)
🎓 Artificial Intelligence
🎓 Biomedical Engineering
🎓 Data Science
🎓 Machine Learning
🎓 Mathematical Modelling
🎓 Software Engineering
deep learning
computer vision
CT MRI analysis
biomarker extraction
cardiac imaging
disease modelling
healthcare AI
image segmentation
interpretable AI
medical AI
PhD project at the University of Auckland applying deep learning to cardiac CT and MRI analysis. Focuses on segmentation, disease modelling, and biomarker extraction to improve diagnosis and clinical decision-making in cardiovascular medicine.
Project Description
This PhD at University of Auckland, within the Auckland Bioengineering Institute, focuses on applying advanced artificial intelligence techniques to cardiac medical imaging.
The research aims to develop deep learning and computer vision models for analysing cardiac CT and MRI data to support improved diagnosis, risk prediction, and treatment planning in cardiovascular disease.
Key research components include:
Cardiac structure segmentation from 3D imaging data
Tissue characterisation and disease phenotype modelling
Spatial biomarker extraction from imaging datasets
Design and training of deep neural networks
Integration of multimodal medical data
Development of interpretable and clinically reliable AI systems
The project emphasises translating computational models into clinically meaningful insights, bridging AI and healthcare applications.
Entry Requirements
Applicants should have:
Background in Computer Science, Engineering, Mathematics, Data Science, Biomedical Engineering, or related fields
Desirable:
Experience in deep learning or computer vision
Programming skills in Python
Familiarity with frameworks like PyTorch
Exposure to medical imaging (CT/MRI) (not required)
Background in Computer Science, Engineering, Mathematics, Data Science, Biomedical Engineering, or related fields
Desirable:
Experience in deep learning or computer vision
Programming skills in Python
Familiarity with frameworks like PyTorch
Exposure to medical imaging (CT/MRI) (not required)
How to Apply
Apply via the University of Auckland postgraduate research portal or project webpage.
Typical documents:
CV
Academic transcripts
Statement of purpose
References
Contact supervisor for details:
Dr J Zhao
Typical documents:
CV
Academic transcripts
Statement of purpose
References
Contact supervisor for details:
Dr J Zhao
Eligibility
UK/Home
EU
International
Supervisor Profile
DJ
Dr J Zhao
The University of Auckland, Auckland Bioengineering Institute
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