Signal Processing and Machine Learning for Biomedical Applications

MARCS Institute for Brain, Behaviour and Development

Lead Researcher: Professor Paul Hurley

About the project

The MARCS Institute for Brain, Behaviour and Development,(opens in a new window) together with the Centre for Research for Data Science and Mathematics at the School of Computer, Data and Mathematical Sciences(opens in a new window) is offering two research scholarships to highly motivated PhD candidates 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 machine learning and 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. Machine Learning and 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. These projects investigate incorporating the physics of ECG sensing (the machine), physiology into the acquisition and interpretation of the mass data available.

The first scholarship is a project together with the Sydney Brain Centre at the The Ingham Institute for Applied Medical Research, and focuses on neurological applications of ECG for early identification of stroke neurology. We may also examine speech/language/facial recognition to link specific neurological clinical presentations of acute stroke with these patterns.

The second research 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 applicants 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.

What does the scholarship provide?

  • Domestic candidates will receive a tax-free stipend of $30,000(AUD) per annum for up to 3 years to support living costs, supported by the Research Training Program (RTP) Fee Offset.
  • International candidates will receive a tax-free stipend of $30,000(AUD) per annum for up to 3 years to support living costs. Those with a strong track record will be eligible for a tuition fee waiver and an Overseas Student Health Cover (OSHC) Single Policy(opens in a new window)
  • Support for conference attendance, fieldwork and additional costs as approved by the Institute.

Eligibility criteria

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.

The successful applicant should:

  • hold qualifications and experience equal to one of the following (i) an Australian First Class Bachelor (Honours) degree, (ii) coursework Masters with at least 25% research component, (iii) a Research Masters degree, or (iv) equivalent international qualifications.
  • demonstrate strong academic performance in subjects relevant to Signal Processing, Data Science, Applied Mathematics, Medicine or related discipline.
  • be enthusiastic and highly motivated to undertake further study at an advanced level.

International applicants must demonstrate English language proficiency.(opens in a new window)

How to apply

Follow the step-by-step instructions on the how to apply for a project scholarship(opens in a new window) page.

  • Note: You do not need to complete 'Step 5: Submit an online application for admission' when applying for this scholarship. You must complete 'Step 6: Submit an online application for a project scholarship'.

Incomplete applications or applications that do not conform to the above requirements will not be considered.

For questions and advice about the research project, please contact the Lead Researcher;
Professor Paul Hurley: p.hurley@westernsydney.edu.au

For questions and advice about the application process, please contact the Graduate Research School: grs.scholarships@westernsydney.edu.au.

Applications close 30 November 2022

*Applications close at 11.59pm Australian Eastern Daylight Time (AEDT).

Scholarship reference codes:
RSP2021_054_MARCS

Physiological and Physics-based Machine Learning for ECG/PPG Emergency Department Triage and Diagnosis

RSP2021_055_MARCS

ECG First-principal Signal Processing and Machine Learning for Neurology