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High Resolution Computational Analysis of the Gastrointestinal Microbiota

Description 
For over 100 years the need to understand particular disease causing, bacterial isolates to treat disease has been clearly understood. Importantly, combining genomics and traditional microbiology, it is now clear that different bacterial lineages and even individual isolates may induce vastly different disease outcomes for patients. While these principles are well established for pathogenic organisms it is now evident that the vast majority of bacterial species with which we are associated likely provide beneficial functions. Similar strain and isolate level understanding are limited by our ability to identify, classify and investigate these species. In the human gastrointestinal tract alone, there are 100 trillion bacteria, representing more than 500 species, that are intimately associated with our daily lives. We have recently development methods to culture the vast majority of the human gastrointestinal microbiota (Nature. 2016) that has unlocked high resolution, whole genome shotgun metagenomics sequencing for detailed analysis. This project will focus on analysis of over 13,000 shotgun metagenomics samples to identify key bacterial species and co-existence networks required for maintenance and reestablishment of health after microbiota perturbation. Please contact Dr Sam Forster (sam.forster@hudson.org.au) for further information.
Essential criteria: 
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords 
computational biology, bioinformatics, metagenomics, microbiota, machine learning, statistics,genomics,phylogeny,ecology,microbiome
School 
School of Clinical Sciences at Monash Health / Hudson Institute of Medical Research » Molecular and Translational Sciences
Available options 
PhD/Doctorate
Honours
BMedSc(Hons)
Time commitment 
Full-time
Top-up scholarship funding available 
No
Physical location 
Monash Health Translation Precinct (Monash Medical Centre)
Co-supervisors 
Dr 
Emily Gulliver

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