PhD Research Project-Developing machine learning methods for drug repurposing in ageing and frailty disease

Details

Ageing is arguably the major biomedical challenge of the 21st century with interventions that extend lifespan and healthspan, and protect against age-related diseases and frailty, being of immense interest. Given the intrinsic difficulties and costs of performing ageing studies in a long-lived species such as humans and even in mammalian animal models, developing predictive bioinformatics methods provides an exciting alternative. In addition, the availability of large amounts of data on ageing-related genes and drugs that target these genes suggests the use of machine learning methods as a cost-effective approach to learn predictive models from such data and generate testable hypotheses. In this project we propose to employ a machine learning approach to predict, among existing drugs, which ones have the greatest probability of being suitable for retarding human ageing and preventing age-related diseases and frailty. Predictions will be tested in both existing cohorts and experimentally in animal models.

Training associated with this project: This is a highly multidisciplinary project at the interface of life and computer sciences. As such, the project will provide a rich and diverse training in several contemporary bioinformatics techniques, AI/machine learning, cell & molecular biology, genetics and biogerontology.

Person Specification

Applications are open to international students, and applicants must not have resided in the UK for more than twelve months in the past 3 years.

Applicants should have a strong background in life or computer sciences and experience in a relevant genomics, bioinformatics or computer sciences field. They should have a commitment to research in ageing and hold or realistically expect to obtain at least an Upper Second Class Honours Degree in a relevant subject.

How to apply

Informal enquiries should be directed to Dr de Magalhaes.

Funding Notes
Funding availability: UKRI/ERC Horizon-Doctoral Network HORIZON-MSCA (Non- UK resident students are eligible).