From a descriptive to a predictive understanding of the human microbiome

Overview

Microorganisms have a profound influence on biological, environmental, and industrial processes, but understanding the complex dynamics of microbial communities and how to manipulate them to our advantage remains a challenge. CMR Director Professor Gene Tyson has recently been awarded a prestigious ARC Laureate Fellowship that aims to overcome current technological limitations and transform microbial ecology from a descriptive to a predictive science. This will be achieved using as a model the most intensively studied ecosystem on the planet: the human gut microbiome.

Research activities

We are looking for motivated PhD students to join the Laureate research team. The team will be led by Professor Tyson and will include a program manager, four postdoctoral researchers and five PhD students who will work closely together to achieve the aims of this ambitious research program. As a PhD student, you will benefit from the mentorship and multidisciplinary expertise of Professor Tyson and the postdoctoral researchers, as well as the state-of-the-art research facilities available at CMR. You will learn broad skills across microbiology, including microbial ecology, multi-omics, biochemistry, molecular biology, and bioinformatics.

Potential focus areas for a PhD project within the program include:

• performing bioinformatics and integrated meta-omic analyses for the longitudinal monitoring of microbiome samples from a large human cohort
• working on a high-throughput cultivation platform for the isolation and characterisation of new species from the human microbiome
• performing gut micro-reactor experiments to test how individual species and entire microbial communities respond to changes in the environment (e.g. temperature, pH) or specific dietary substrates (e.g. polyphenols, fibre)
• applying statistical and machine learning methods to assign putative functions to unknown proteins and to develop predictive models for the gut microbiome.

Outcomes

The fellowship program will deliver new tools for integrated meta-omic analysis, a biobank featuring thousands of novel microorganisms from the human gut, and machine learning models to predict how entire microbial communities will respond to changes in their environment.

Skills and experience

Candidates are expected to have obtained a first class honours (or equivalent) undergraduate degree in microbial ecology, molecular biology, bioinformatics, or a related discipline.

Scholarships

You may be eligible to apply for a research scholarship.

Explore our research scholarships

Keywords

• microbiome
• machine learning
• meta-omics
• microbiology

Contact

Contact the supervisor for more information.