Predicting how disease evolves — not just who gets it

This project advances genetic risk prediction by focusing on disease progression rather than onset. It will develop and validate progression-specific polygenic risk scores (PRS) trained on longitudinal data for glaucoma, age-related macular degeneration (AMD), and colorectal cancer. The study uses repeated clinical measurements and genetic data to isolate genetic contributions to the rate of disease worsening, enabling personalized treatment and surveillance. What You Will Do Conduct PhD-level research developing statistical genetics methods and applying progression PRS to longitudinal cohorts from ophthalmology and oncology. Train in statistical genetics and longitudinal analysis methods working within a multidisciplinary team alongside epidemiologists, clinicians, and biostatisticians. Collaborate internationally and contribute to translational genomics research informing clinical applications. Expected Outcomes Develop novel PRS models predicting progression rates of glaucoma and AMD, and cancer risk from polyps. Validate PRS utility for clinical decision-making including treatment selection and surveillance interval personalization. Produce insights transferable across diseases and contribute methodological innovations in genetic epidemiology. Why It Matters Accurate prediction of disease progression can transform clinical care by enabling early intervention and tailored treatment strategies. This innovative work meets urgent clinical needs beyond disease risk to addressing severity and progression, with broad translational potential in eye diseases and cancer.

Essential: Strong undergraduate or Masters degree in genetics, epidemiology, statistics, bioinformatics, or related quantitative discipline. Enthusiasm for large-scale human genetic and clinical datasets. Desirable: Experience with R or Python; familiarity with GWAS or epidemiology methods; interest in translational genomics.