Location: | London |
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Salary: | £43,093 to £50,834 per annum or £38,194- £41,388 per annum (Research Assistant scale) |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 23rd March 2023 |
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Closes: | 20th April 2023 |
Job Ref: | MED03748 |
Location: St Mary’s Hospital Campus, School of Public Health.
Job Summary
This job is an opportunity to join the School of Public Health, Department of Epidemiology and Biostatistics, Imperial College, and work in the Computational Epidemiology team of Prof M Chadeau-Hyam and work on the EU funded EXPANSE project. This is an exciting and innovative project that combines statistics, machine learning, environmental and social sciences as well as molecular medicine to investigate drivers of cardiometabolic health. Research focuses on integrating Exposome datasets featuring a large number of measurements and/or observations, to better understand the lifestyle, environmental, metabolic, and genetic causes of chronic disease, as well as understanding the features of the exposome that are driving the quality of ageing and individual risk of adverse conditions. This work will be done under the direct supervision of Prof M Chadeau-Hyam, leading the statistical workpackage of the project, and the post holder will report to Prof M Chadeau-Hyam and Dr Dragana Vuckovic.
Duties and responsibilities
You will be responsible for the development of advanced machine learning and statistical models to identify biologically imprinted effects of external (blocks of) exposures, their evolution in the life course and the contribution of other compartments of the exposome to these signals. Resulting 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 a longitudinal component to account for full history and for life stages at which individuals may be more susceptible or vulnerable.
Essential requirements
You will be constructing and applying machine learning and statistical models using OMICs data, biochemistry and social factors in the life course in a longitudinal set up and investigating their effect on health and ageing by:
You will have:
Further Information
This role is full time and fixed term until 31st Dec 2024. This role is based at St Mary’s Campus.
Should you require any further details on the role please contact: Prof. Marc Chadeau-Hyam – m.chadeau@imperial.ac.uk
To apply, visit www.imperial.ac.uk/jobs and search by the job reference MED03748.
Closing date: 20/04/2023
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