My current research focuses on resilience, which is the process by which individuals can maintain positive health and functioning after facing stress or adversity. In particular, my work focusses on two main types of resilience, these being psychological resilience (the maintenance of psychological functioning following stress) and cognitive resilience (the maintenance of cognitive functioning following stress). 

My PhD project aims to identify genes and brain features influencing these different types of resilience and combine this information with clinical variables in machine learning algorithms in order to predict resilience. 

The associated genes and brain features may assist in identifying major pathways involved in resilience, helping to inform future interventions. The predictive algorithm may then allow identification of individuals with low resilience who might benefit the most from these interventions, with the ultimate goal being to help promote positive outcomes across a person's life after the experience of adversity. The findings will also help disentangle different biological mechanisms underpinning different types of resilience.