Parasitic worms (helminths) cause some of the world’s most neglected diseases, affecting billions of animals and people worldwide. Despite efforts to control these insidious diseases, no commercial vaccines are available, current diagnostic methods are inadequate, and treatment relies heavily on only a small number of drugs. Because drug resistance is a major threat, there is an urgent need to develop new interventions.
Published draft genomes and transcriptomes provide a solid basis for drug target discovery, exploring the biology of parasites and the pathogenesis of disease. However, most draft genomes are fragmented due to an inability of second-generation (i.e. short-read) sequencing technologies to assemble across repetitive DNA regions, which constrains annotations and in silico analyses. To address this limitation, long-read sequence data is being used to substantially improve the assembly and gene prediction to produce high quality reference genomes for eukaryotic pathogens. In this project, you will work on the automation of bioinformatics pipelines for reproducible genome assembly using high quality long- and short-read sequence data, and accurately predict the genes in complex parasite genomes. The goal is to achieve the genome quality standards set by the NIH-NHGRI in the USA.
This project requires extensive experience in computation biology/bioinformatics but is open to applicants with a biological, statistics and/or computer science background.
Although a PhD scholarship stipend (AUD 32,304 pa) is available for this project, the eligible applicant will apply through The University of Melbourne Postgraduate Research Scholarship system. Information on how to apply is available upon request.