Research Supervisor Connect

Neural Correlates of Chronic Cardiovascular Disease


Chronic cardiovascular disease (diabetes, obesity, heart disease) has a wide systemic physiological impact, including microstructural damage to the brain. Our group has an opportunity for a PhD student to investigate the impact of these conditions on brain structure and function using our large database of MRI scans. The project will use structural imaging with cutting-edge MRI techniques including multi-shell multi-band diffusion imaging, diffusion kurtosis imaging and tractography, but could also include analysis of our multi-band functional MRI data and others. The project will involve assisting with the acquisition of data from test subjects, analysis of imaging and neuropsychological data and publication. The student will leverage our existing automated processing pipeline.
Our imaging database currently has 2000+ datasets, and is expected to grow to over 3000 in the coming years. The group is based in the Charles Perkins Centre at the University of Sydney, Australia. Our other topics of research include imaging of: mTBI, depression, chronic cardiovascular disease, 4D flow of the heart and motor neurone disease. We have recently acquired the highest-ever resolution image of the brain, and are applying this methodology in our Chronic Diseases Connectome Project (CDCP) - designed to acquire over 1000 subjects with risk factors or a diagnosis of diabetes, obesity, or heart disease. Our group is also pursuing a number of concurrent projects in concussion and depression.
The prospective student will have prior experience of quantitative image analysis and an interest in the clinical research questions surrounding brain injury in chronic cardiovascular disease.


Professor Stuart Grieve.

Research location

Newtown - Heart Research Institute

Program type



This PhD project focusses on the relationships between brain imaging, clinical and neuropsychological outcomes in chronic cardiovascular disease using state-of-the-art MRI acquisition and analysis techniques in a large cohort.

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Opportunity ID

The opportunity ID for this research opportunity is 2412

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