Prestigious Scientia PhD Scholarships on Using Big Data to Redesign the Health System

Prestigious Scientia PhD Scholarships on Using Big Data to Redesign the Health System

Tuesday, July 04, 2017

Applications for the prestigious UNSW Scientia Ph.D. Scholarship Scheme on the project "Using Big Data to Redesign the Health System" are now open.

The UNSW Scientia Ph.D. Scholarship Scheme is the most prestigious and generous scholarship scheme at UNSW and it aims to attract the best and brightest people into strategic research areas. Awardees receive a $50,000 scholarship package for four years, comprising a $40,000 per annum tax-free stipend and a travel and development support package of up to $10,000 per annum. International students also receive a tuition fee scholarship.

In addition to this scholarship package, scholars are provided with access to a range of development opportunities across research, teaching and learning and leadership and engagement

Applicants should submit their expression of interest at

by 21st July 2017 but are encouraged to do so as early as possible.

 More information on the UNSW Scientia PhD Scholarship Scheme:

Information about the project

Health services are working to develop new models for care that keep people out of hospital, such as community outreach, daily outpatient assessment and hospital in the home. Identifying patient subgroups ('phenotypes') with distinct characteristics that are predictive of their subsequent outcomes (e.g. admission, complications) is key to designing these new models. Machine learning (ML) techniques are data-driven approaches that can discover statistical patterns in high-dimensional, multivariate data sets. This project will apply ML techniques to health 'big data' to identify patient phenotypes that will support the design and implementation of new tailored care pathways for patients with chronic disease.

Supervisory Team

The successful applicant(s) will be supervised by Prof Louisa Jorm (Director, Centre for Big Data Research in Health, and Dr Peter Straka (DECRA Research Fellow in Statistics, Please contact Louisa Jorm <> for more details.



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