The MARCS Institute for Brain, Behaviour and Development together with the Centre for Research for Data Science and Mathematics at the School of Computer, Data and Mathematical Sciences is offering a research scholarship to highly motivated PhD candidate to join a growing dynamic research group on signal processing, machine learning and imaging science for biomedical applications.
This is an excellent opportunity to master theory and fundamentals of signal processing algorithms, analyse data and experiment using medical devices, all the while getting to interact with clinicians on the ground and seeing your work progress to being applied in a hospital context.
There is a lot more variation in an ECG signal than can be processed by a clinician. Signal Processing techniques offer great promise to improve diagnosis quickly and improve outcomes. AI/ML however cannot on its own help with interpretation and generalisation. This project investigates incorporating the physics of ECG sensing (the machine), physiology into the acquisition and interpretation of the mass data available.
This scholarship is a project together with South-Western Sydney Local Health District at Liverpool Hospital, and focuses on cardiology, specifically on cardiovascular pattern recognition in ECGs. There have already been exciting developments in simpler ECG acquisition in the smart watch and device space. Beyond analysing existing acquired ECGs, this is an opportunity to adapt how ECGs are obtained in the first place, to maximise information, speed things up, and improve diagnosis.
The successful applicant will combine their time working at the new world-class research facility in Westmead, Sydney and at the Ingham Institute and Liverpool Hospital in Sydney. Please feel free to express a preference for a particular scholarship in your application letter.
We welcome applicants with a background in Data Science, Machine Learning, Applied Mathematics, Signal Processing, Electrical Engineering or related disciplines, or someone from Medicine with stronger technical and abstraction skills.
If interested, please apply directly through the university application process at https://bit.ly/3EGtm1l. You do not need to email the insttitution or supervisors. The step for a support letter should be ignored, as this applies only to general scholarships, and not this project scholarship.
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