School of Medicine
The School of Medicine is a leading provider of medical education and medical research in Queensland, with the country's largest medical degree program. The program includes graduate entry and school-leaver entry streams, and is an integrated, case-based/problem based learning program. The School is a diverse enterprise operating over multiple sites, with Queensland Health and private health service providers as major partners. Geographically, the School extends throughout Queensland with major sites in Brisbane, the outer metropolitan areas, and a number of rural and remote area facilities throughout the rest of the state. The UQ medical degree is also delivered on the UQ Ipswich campus to the west of Brisbane, and we are also scoping expansion on the Sunshine Coast. More information about the School of Medicine can be found at http://www.som.uq.edu.au/.
Surgical Oncology Group is part of The University of Queensland School of Medicine and is located within the Translation Research Institute on the Princess Alexandra Hospital campus. The aim of the Group is to study the genomic aberrations that underpin the development and progression of oesophageal cancer and seeks to develop strategies for personalized therapies for this poor prognosis cancer.
The successful Scholar will pursue a PhD degree in biomedical research whereby they will develop bioinformatics skills for the discovery of genetic biomarkers for disease onset, prognosis and personalised treatment in cancer.
The goal of this project is the development of novel biomarkers that help clinicians to optimally treat patients with oesophageal adenocarcinoma. Cancer is a complex genetic disease, or rather thousands of different diseases. Cancer is induced by genetic mutations and each cancer has its own individual mutation profile. No two cancers are alike but cancer treatment has been a one-size-fits-all solution. The goal of this research is the discovery of novel biomarkers to predict patient prognosis and who will respond and benefit from a specific treatment, together leading to a personalised and optimal cancer therapy.
Identification of novel genetic biomarkers for prognosis, survival and personalized treatment in cancer.
Using Bioinformatics and statistics, genomic mutations and epigenetic changes in oesophageal adenocarcinoma tumours are identified. Together, these may be used as markers to guide clinicians in the choice of an optimal treatment strategy that best matches the molecular characteristics of the individual patient. Advanced computational method are applied to identify complex associations between genomic mutations and a patients treatment outcome, methods that are also used for predicting stock market prices or for weather forecasts. Heterogeneous datasets are analysed in an integrative approach, including genomic variations, epigenetic modifications, gene expression changes and copy number variations. For the discovery of novel biomarkers various machine learning and data-mining methods are employed, such as Support Vector Machines, network analysis, Cox models, regression models, supervised and unsupervised clustering, and multivariate techniques. Novel visualisation techniques for the integrative analysis of heterogeneous datasets (including gene expression changes, epigenetic modifications and genomic variations) will be developed.
The candidate will have a 1st Class Honours degree or equivalent in science or medicine and a strong motivation to pursue a PhD degree. Prospective students will be provided with assistance in applying for admission to a PhD. Applicants should have knowledge in bioinformatics and molecular biology.
The base stipend will be at the rate of AUD$29,464 per annum (2014 rate) tax-free for three years with the possibility of a six month extension in approved circumstances. For information about applying for admission and for the full terms and conditions, please visit the UQ Graduate School website at http://www.uq.edu.au/grad-school/how-to-apply.)
For further information about the research project, please contact Associate Prof Andrew Barbour (email@example.com).
All applicants must supply the following documents: Cover letter, CV/Resume and Academic Records (indicating GPA scores/grades).