Systems immunology and multi-omics approaches to understand protective immunity to human malaria

This PhD project aims to develop and apply computational approaches that integrate systems biology and molecular immunology to understand host-pathogen immunity and predict immune control of malaria. The project will utilise systems-based immunology and multi-omics approaches to profile the host immune response in controlled infection models of malaria at molecular, cellular, transcriptome and proteome-wide scale.

The overall aim will be to develop and apply omics-based technologies and computational tools, including network theory and machine learning, to integrate multiple high-dimensional datasets and reveal novel insights into host-pathogen immunity and predict immune responsiveness and parasite control. Modelling of large-scale existing datasets, including those generated by single-cell RNA-sequencing technologies, may also be a feature of this project. The opportunity to identify new knowledge and integrate this with experimental data produced by our laboratory will be instrumental to extending the impact of these bioinformatics analyses. This project will provide an opportunity to be at the forefront in cutting-edge technologies and advances in computational analysis of integrated high-dimensional omic data.

Methodologies:

Bioinformatics, Machine Learning, Immunology, Systems Immunology, Systems Biology, Genomics/Proteomics/Transcriptomics, Molecular and Cell Biology, Statistics

Eligibility:

Entry: BSc Honours Class I (or equivalent via outstanding record of professional or research achievements)

Experience/Background: Experience with programming languages, mathematics, statistics and/or background in immunology and molecular sciences, with an interest in integrating the fields of immunology and bioinformatics.

Excellent computer, communication, and organisational skills are required. Forward thinking, innovation and creativity are encouraged.