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ABOUT THE ROLE

This job is an exciting opportunity to join the School of Public Health, Department of Epidemiology and Biostatistics at Imperial College, and work within the multidisciplinary Computational Epidemiology group of Prof M Chadeau-Hyam on the EU-funded STAGE project. This is an innovative project that combines statistics, machine learning, environmental and social sciences as well as molecular medicine to investigate ageing and its health outcomes. The work aims to better understand the features of the exposome that drive the quality of ageing and individual risk of adverse conditions. This work will be conducted under the direct supervision of Prof. M. Chadeau-Hyam and Dr Dragana Vuckovic, who will lead the statistical work package of the project.

WHAT YOU WOULD BE DOING

You will be responsible for the development of advanced statistical models and machine learning algorithms to identify (i) biologically imprinted effects of external exposures, (ii) their evolution in the life course and the contribution of other compartments of the exposome to these signals. Resulting statistical models should also facilitate the identification of molecular signatures of shared exposome types and their trajectories throughout the life course. The goal is to incorporate in high throughput profiling techniques, (i) both a causal and mechanistic component to explore mechanisms mediating the biological effect of individual experiences, and (ii) a longitudinal component to account for full history and for life stages at which individuals may be more susceptible or vulnerable.
You will report to Prof M Chadeau-Hyam and Dr D Vuckovic and you will have the opportunity to contribute to other large-scale international projects involving the group as well as to teaching and supervision of MSc students from the Health Data analytics and Machine Learning programme.