Centre for Big Data Research in Health – Scientia Scholarships

Applications are now open for the prestigious UNSW Scientia PhD Scholarship Schemes on big data projects led by the Centre for Big Data Research in Health.

The UNSW Scientia PhD 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 - 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, scholars are provided with access to a range of development opportunities across research, teaching and learning and leadership and engagement.

The multi-disciplinary supervisory teams have been selected based on their demonstrated capacity in excellence in research and high quality supervision, plus their commitment to developing and mentoring PhD scholars.

More information about the projects:
Genomic determinants of basal cell carcinoma (BCC) susceptibility
This multi-disciplinary collaboration includes cancer scientists at the Centre for Big Data Research in Health, the Garvan Institute and the Sydney School of Public Health.
Basal cell carcinoma is the most common and costly cancer in Australia. It may also be a marker of general high cancer-risk. Sun exposure is an established cause, but the underlying genetic determinants and molecular pathways are unknown. We will reveal the complete DNA sequence of 2000 well characterised individuals with and without this cancer using state-of-the-art whole genome sequencing.

Whole genome sequencing is unprecedented in its genomic sequencing coverage and accuracy. We have developed novel computational pipelines and other biostatistical and analytical tools that will aid discovery of the key biological processes underlying the development of BCC. We will apply this new knowledge to increase the accuracy of risk prediction models for BCC. Identifying functional, clinically actionable genetic variants will create new opportunities for the prevention, screening and treatment of not only BCC but also for the wide range of internal malignancies for which these individuals face an elevated risk. The very high burden and cost of BCC means that even modest reductions in these tumours from this new knowledge would result in important reductions in morbidity and health care costs.

This project would suit applicants with training and/or experience in bioinformatics, genetics or biostatistics.

Using Big Data to Redesign the Health System
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.

Applicants should submit their expression of interest by 21st July 2017 but are encouraged to do so as early as possible. Go to

More info about UNSW Scientia PhD Scholarship Scheme:
* General info http://www.2025.unsw.edu.au/apply/

* Guidelines http://www.2025.unsw.edu.au/apply/node/69/

* FAQs: http://www.2025.unsw.edu.au/apply/unsw-scientia-phd-scholarships-faqs