Allergies and autoimmunity are complex immune system aberrations. Both involve multiple immune cell populations coordinating across several organs of the body. The growing prevalence of these debilitating conditions across the population demands urgent solutions to improve quality of life. However, the requisite knowledge needed to develop and optimise treatments and preventative measures remain elusive. Ultraviolet light exposure treatments have shown promise in alleviating symptoms in both these diseases. Yet, the manner in which these treatments holistically impact the immune system and its myriad feedback and regulatory pathways are unknown, holding back wide-scale clinical deployment.
Whilst powerful high-throughput techniques proffer unprecedented characterisations of immune cells and their interactions, this data alone does not yield understanding and insight. Novel computational approaches, founded in machine learning, to integrate and extract patterns from high throughput data are needed. Embedding the resulting insights into integrative computational modelling provides a powerful platform in which to explore novel treatment strategies and optimise them for a specific patient. Computational models offer an unparalleled scope for nuanced experimental manipulation, and any aspect of the system can be quantified. This project will explore the dynamics of individual cell populations and how they interact with one another to map out their roles in these diseases. The resultant tools constitute an invaluable complement to conventional wet-lab work.
This highly interdisciplinary project will closely align with clinicians and immunologists studying both multiple sclerosis and contact dermatitis. The candidate will be based at the University of Sydney's flagship interdisciplinary research centre, the Charles Perkins Centre, where they will be embedded with biologists and modellers alike. The project will develop the aforementioned computational capacity to investigate the onset, persistence and possible treatment strategies for these diseases. If successful, the work can be rolled out to studying other diseases. The work spans bioinformatics, machine learning and computational agent-based modelling, with potential to gain wet-lab or immunological experience if the candidate so desires.
The immune system, and its role in disease, epitomises complexity. Novel computational, mathematical and statistical techniques are needed to complement high-throughput technologies and generate integrative understanding. This project develops such methodologies to study the pathogenesis and possible treatment of Multiple Sclerosis and Contact Dermatitis. This is the forefront of interdisciplinary research. You will work closely with biologists, clinicians, mathematicians and computer scientists, all of whom are located in the same offices and interact on a daily basis.
Additional supervisors Scott Byrne, Felix Marsh-Wakefield
In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:
The opportunity ID for this research opportunity is 2478