Available student projects

Community-level factors contributing to optimal nutrition and health across the lifespan

Available as: Masters by Research and PhD

Dr Catherine Paquet

Research projects are currently available to be embedded in a program of research on (1) the associations between attributes of the food/nutrition environments (e.g. presence of food outlets, marketing strategies) or the social environment on dietary behaviours and health outcomes across the life course and (2) identification of individual factors explaining differences in responsiveness to environmental factors. Projects will make use of existing observational cohort data.Please see current research projects for more information.

Determinants of adverse patient-reported outcomes in cancer survivors

Available as: Masters by Research

Dr Terry Boyle

This project will use data from a cohort of 500 cancer survivors (breast cancer, colon cancer and non-Hodgkin lymphoma). Baseline assessment in 2013- 14 involved collection of sleep quality/duration, sedentary time and physical activity (assessed with an accelerometer), clinical, demographic and lifestyle factors, and patient-reported outcomes (health-related quality of life, fatigue, depression, cognitive functioning & unmet needs). Follow-up data on patient-reported outcomes was collected in 2017.

Potential projects include:

  1. Examining associations between sleep, sedentary and active behaviours and changes in patient-reported outcomes
  2. Investigating determinants of poorer patient-reported outcomes and unmet needs.

Disease Prevention with Precision: Identifying and Overcoming Individual Genetic Vulnerabilities

Available as: Masters by Research and PhD

Professor Elina Hyppönen

The Nutritional and Genetic Epidemiology Group has several opportunities for Masters by Research and PhD projects in the broad area of “Precision Health”. Projects are suited for health professionals, keen to obtain high calibre research training and to continue professional development by acquiring skills for assessing large pools of information from the viewpoint of an individual patient.

Studies are based on large datasets with detailed information on genetics, lifestyles and health and include:

  1. Vitamin D supplementation: is it beneficial or even safe? (top-up scholarship of $20k/pa available)
  2. Improving risk prediction to prevent cancer
  3. Diet and cancer: establishing genetic evidence for a causal association
  4. Phenome-wide study on physical activity and health

Mapping socio-demographic, lifestyle, and environmental factors for non-communicable diseases and its progression

Available as: Masters by Research and PhD

Dr Ming Li

The prevalence of non-communicable diseases such as overweight and obesity, diabetes, coronary heart diseases, kidney dysfunction, and cancer is on the rise. These health conditions have become major causes of excessive early death and a burden to our society. Evidence suggested early-life experience, and behavioural lifestyle, and environmental factors are associated with them. But the evidence is scattered and segmental in terms of disease natural history and does not provide an overall picture of the risk factors due to pitfalls in study design, financial restriction, or other barriers. The proposed PhD project is to map socio-demographic, individual lifestyle, environmental factors along the disease progression in a national cohort that links with population-based administration data.

Personalised precision medicine using a statistical approach based on whole-genome information

Available as: Honours, Masters by Research or PhD

Dr Hong Lee

The genomic era provides a realistic opportunity for precision medicine in which individuals are classified into high or low-risk sub-groups based on profiles that incorporate information from genomic risk factors. Precision medicine based on genomic risk prediction can be applied at an early stage. It may be possible to predict future disease risk at birth, with potential to predict, and to intervene, to prevent progression to the disease. However, the accuracy of genomic risk prediction using current approaches is not yet good enough to be applied to an intervention program for complex diseases. In this project, we will investigate a number of novel approaches to increase the accuracy of genomic prediction. We will also estimate economic benefits from reduced treatment costs in an intervention program implementing novel genomic prediction approaches. The outcomes of this project will be of great significance to the prospects of using genetic information for personalised precision medicine. This project will be suitable for a high achieving student who has interest in complex statistical modelling, and in developing related skills with an application to disease prevention.

Understanding the Genetic Architecture of Complex Diseases by Gene-Environment Interaction

Available as: Honours, Masters by Research or PhD

Dr Hong Lee

Recent studies provide theoretical and empirical evidence that both nature and nurture play important roles in the genesis of human complex disorders. Additional genetic and environmental factors can be identified in studies that examine gene-environment (G x E) interactions. G x E interaction research has the potential to provide important insights into biological mechanisms and strategies for disease prevention and control. Participating students will use linear mixed models to analyse existing Genome-Wide Association Studies (GWAS) data related to some common health problems such as obesity, cancer and mental disorders, and examine how different genotypes respond differently to environmental changes. Students will also make profile scores based on the results for independent sample to quantify their individual risks. We are a strong statistical genetics team that will provide students extensive trainings in advanced statistical techniques and related software such as PLINK, GCTA and MTG2. PhD students are expected to have some statistical knowledge including hypothesis testing and regression modelling as well as computer programming skills (e.g. R).

Using large-scale genomic and other omics data to dissect the biology of complex traits and diseases

Available as: Honours, Masters by Research or PhD

Dr Beben Benyamin

The broad aim of the research project is to understand the aetiology and biological mechanism underlying complex traits and diseases, such as schizophrenia and motor neuron disease through the use and development of advanced statistical methods applied to high throughput genomics and clinical data.

Some examples of available student projects are:

  1. The application of statistical genomic methods on large-scale ‘omics’ (e.g. genomics, epigenomics, transcriptomics) data to understand the causes of neuropsychiatric diseases, such as motor neuron disease or schizophrenia
  2. Trans-ethnic genomic analyses to dissect the transferability of genomic findings in European samples into other populations, such as Asians
  3. Mendelian randomization methods to infer the causal roles of modifiable risk factors (such as smoking) on complex diseases
  4. Using genome-wide genotype data to dissect the heterogeneity of complex diseases.

It is now recognised that with the availability of big omics and health data, the major limiting factor is the availability of highly trained scientists who can ask the right questions and are equipped with the appropriate specialised computing and statistical genomic capabilities.

By studying with our group, you will have opportunities: to learn or develop the latest statistical genomic methods applied to large scale omics data, learn to analyse big data in genomics using computer program, and equip yourself with the rare set of skills required in the era of personalised and precision health.

Using mixed reality and holographic technologies (iHealth) for delivery of smoking cessation treatment among patients admitted to hospital with tobacco-related illnesses

Available as: Masters by Research and PhD

Associate Professor Kristin Carson-Chahhoud

Establish a foundation for iHealth tools to aid delivery of smoking cessation treatment for patients admitted to hospital with smoking related illnesses. This will be achieved through two stages:

  1. Development of 3 iHealth smoking cessation resources for smartphone delivery, including one with augmented reality, one with virtual reality and one with holographic technology.
  2. Evaluation of the practicality and feasibility of these smoking cessation resources for use by smokers admitted to hospital with tobacco related illnesses, ex-smokers and health professionals via qualitative research including focus groups and one-on-one interviews.