PhD Scholarship: Machine learning for medical signals

A PhD scholarship is available to support a computer science, mathematics, or similar science graduate to study rich medical data streams associated with ICU (intensive care) patients using the tools of machine learning.

Patients in an ICU are hooked up to a range of sensors, yet much of the waveform data that results is essentially lost, other than snapshots at specific moments. The PhD project is to construct machine learning methods for such waveform data – in particular, generative models built using unsupervised learning. These will facilitate better visualisations of data that is changing, and automated detection of clinically important changes in the waveform without generating excessive false positives.

The project will be carried out under the supervision of Associate Professor Marcus Frean and Professor Stephen Marsland at Victoria University of Wellington. The student will join a larger team within Victoria working on related projects, with input from the clinical team in the ICU at Wellington hospital ensuring we remain linked to the real questions of medical relevance.
Eligibility
Applicants should have a strong numerate background (ideally have a First-Class honours degree in Computer Science, Mathematics, or a similar discipline), and satisfy the University of Victoria’s entry requirements for PhD study.
Total value
The three-year scholarship covers PhD tuition fees for a domestic or international student plus a non-taxed living allowance of NZ$27,300 per annum. The starting date can be anytime between November 2017 and 1 March 2018.
How to apply
For further information and to apply, please contact:
Associate Professor Marcus Frean
Te Pūnaha Matatini
Victoria University of Wellington
New Zealand
[Email Address Removed]