Centre for Population and Disease Genomics - Earmarked
Genetics of sensory nutrition – using genetics to understand how taste and olfactory perception influences eating behaviour and health
Principal Advisor: Dr Daniel Hwang (IMB)
This project requires candidates to commence no later than Research Quarter 3, 2025, which means you must apply no later than 29 February 2024.
Human perception of taste and smell plays a key role in food preferences and choices. There is a large and growing body of work suggesting that taste and smell (together known as "chemosensory perception") determine eating behaviour and dietary intake, a primary risk factor of chronic conditions such as obesity, cardiometabolic disorders, and cancer.
However, evidence to date is largely based on observational studies that are susceptible to confounding and reverse causation, leaving the "causal effects" of chemosensory perception on food consumption unclear. If their relationship is truly causal, flavour modification may represent a tangible way of modifying food consumption in a way that benefits public health outcomes.
This PhD project aims to: (i) elucidate the genetic architecture underlying individual differences in taste and smell perception, (ii) use this information to assess their causal effects on eating behaviour, and (iii) create a sensory-food causal network mapping individual sensory qualities (i.e. sweet taste, bitter taste, and more) to individual food items.
The candidate will gain skills in big data analyses, computer programming, statistical method development and application (structural equation modelling, genome-wide association analysis, Mendelian randomisation), and writing and publishing scientific peer-reviewed papers. The candidate will also have opportunities to be involved and to lead national and international collaborative projects.
*Qualifies for an Earmarked Scholarship.
Sometimes Correlation does Equal Causation: Developing Statistical Methods to Determine Causality Using Genetic Data
Principal Advisor: Prof David Evans (IMB)
This project requires candidates to commence no later than Research Quarter 1, 2024, which means you must apply no later than 30 September, 2023.
There is a well-known mantra that correlation does not necessarily equal causation. This is why randomized controlled trials in which participants are physically randomized into treatment and placebo groups are the gold standard for assessing causality in epidemiological investigations. However, what is less appreciated is that strong evidence for causality can sometimes be obtained using observational data only. In particular, genotypes are randomly transmitted from parents to their offspring independent of the environment and other confounding factors, meaning that genotypes associated with particular traits can be used like natural “randomized controlled trials” to examine whether these traits causally affect risk of disease.
The aim of this PhD project is to develop statistical methods to assess causality using observational data alone. The successful candidate will gain experience across a wide range of advanced statistical genetics methodologies including Mendelian randomization (a way of using genetic variants to investigate putatively causal relationships), structural equation modelling, genome-wide association analysis (GWAS), genetic restricted maximum likelihood (G-REML) analysis of genome-wide data which can be used to partition variation in phenotypes into genetic and environmental sources of variation, and instrumental variables analysis (using natural “experiments” to obtain information on causality from observational data). The candidate will apply the new statistical methods that they develop to large genetically informative datasets like the UK Biobank (500,000 individuals with genome-wide SNP data).
*Qualifies for an Earmarked Scholarship.
Testing effect of environmental exposures on subsequent human generations
Principal Advisor: Dr Gunn-Helen Moen (IMB)
This project requires candidates to commence no later than Research Quarter 1, 2024, which means you must apply no later than 30 September, 2023.
This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.
We are seeking a PhD candidate to join our research team in this exciting project funded by the Australian Research Council. The research group has conducted work within genetic epidemiology, focusing on pregnancy related exposures and outcomes.
Depending on the student’s level of experience and aptitude, they will help develop and/or apply statistical genetics approaches to investigate the possible existence of transgenerational epigenetic effects on human phenotypes.
A PhD is about learning new skills and learning how to do research. Our ideal candidate will have knowledge or keen interest in learning genetics, epidemiology, statistics, unix and shell scripting, and statistical software such as R. You will work closely with an experienced researcher on the project. There will also be possibility for a research stay in Norway during this PhD.
The main purpose of the fellowship is research training leading to the successful completion of a PhD degree.
The advertised projects are fundamentally quantitative and computer-based, and so evidence of aptitude in these areas is essential. The candidate should also have the ability to design, plan, and execute experiments and be proficient in English, both written and oral.
We are looking for someone who is:
- Excellent communication and team working skills
- Organized and structured
- Flexible
- Enthusiastic and willing to learn new methods and techniques
*Qualifies for an Earmarked Scholarship.