Risk Models for non-communicable disease (NCD) in Women

Project #1: Developing Risk Models to Reduce Population Attributable Risk (PAR) in Female NCD Type: PhD (Full-time) Start Date: Flexible Project Summary: Join our nationally recognised team to develop and validate risk prediction tools for NCD in women, integrating neuroendocrine markers, hormone therapy, and lifestyle predictors. WHO noted NCD as the greatest future challenge globally and leading causes of death and disability are NCD (Heart Disease and Dementia, Osteoporosis, Osteoarthritis, Depression) are all more common in women than men, as sex-specific factors have been under researched and important sex differences are now acknowledged. The goal is to demonstrate a reduction in population-attributable risk (PAR) by enabling precision prevention strategies. Using advanced traditional statistical methods and machine learning (e.g., XGBoost, Random Forests), and TRIPOD-AI frameworks, you will build models with real-world impact. Highlighting the importance of statistical methodologies when planning public health intervention. What You Will Do: · Synthesise predictors from rich datasets (WHAP, MBS/PBS) · Apply AI & statistical methods to develop risk models · Validate models in national and international cohorts · Assess modifiable risk impact on PAR using simulation Who We're Looking For: We are looking for TWO PhD candidates to work in this large research program. Candidates with expertise in biostatistics, data science, AI/ML, and an interest in women’s health, precision medicine and prevention.