PhD Studentship : Mental health Data Science: Fully Funded PhD Studentship in Machine learning modeling of self-harming and suicidal behaviors based on country- and person-level indicators

Swansea University - Medical School

Proposed topic “Creating a National Digital Twin for self-harming and suicidal behaviours”

Self-harm and suicide are increasingly recognized public health priorities globally, leading to greater political commitment and a surge in scientific inquiry. However, the wide range and vast number of influencing factors makes understanding, preventing, and treating these behaviours highly challenging. This is further hindered by a lack of diverse big data resources and matched, powerful analytical tools. As a result, progress in the field has been characteristically slow over the last 50 years.

The National Centre for Suicide Prevention and Self-harm Research (NCSR) is tackling these barriers by putting together a world-leading data resource on suicide and self-harm, and powerful machine learning methodologies compatible with epidemiological principles to produce high-quality evidence and tools.

In this inter-disciplinary PhD project, you will collaborate with other researchers from the NCSR in the above mission. You will:

• Help collate data resources relevant to suicide and self-harm.
• Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and others) compatible with epidemiology.
• Produce a digital twin for national suicide and self-harm rates.

You will expand your data wrangling, analytical and programming skills on python and develop expertise in the fields of machine learning, epidemiology, big data analysis, and suicide and self-harm.

Your work will expand the frontier of machine learning applications in epidemiology and improve our understanding of suicide and self-harm. It will also directly inform the development of a support tool to design targeted interventions, efficient policies and national strategies. Above all, your work will be in a privileged position to have a real-world impact, helping improve the life of those most vulnerable.