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PROJECT TITLE

Stratifying Menopause Patients towards a personalised medicine approach

SUPERVISORS

DESCRIPTION OF PROJECT

Menopause carries with it a set of symptoms that can have a significant impact on a patient's quality of life: hot flushes, cognitive disruption, and psychological changes amongst others. The severity of these symptoms exists across a spectrum: some patients will be minimally affected, whilst others report disruption to their ability to work, socialise and maintain normalcy in their relationships. Menopause patients are currently largely treated as a homogenous group, however symptom type, onset, duration, and treatment susceptibility show large variation. The increasing use of electronic healthcare systems, and their availability as a research resource offers the ability to look at this multivariate, complex process in new ways.

This project aims to utilise longitudinal electronic healthcare data in the UK Biobank and apply high dimensional data methodology including machine learning and statistical genetics to identify subgroups of menopause patients and understand the biological pathways underlying them. In this project you will: 1) Utilise novel machine learning on multimodal data to identify subgroups of menopause patients. 2) Identify clinical features associated with the subgroups. 3) Endeavour to understand the biology underlying the differences between the groups using biochemical data including genetics and omics data.

Together, this project looks to develop a more granular, data-driven, understanding of menopause and move towards a personalised medicine approach of its treatment.

TRAINING OPPORTUNITIES

  • Research training in machine learning, statistics, quantitative genetics and beyond
  • Membership to journal clubs and research group meetings to understand current research landscape, cutting edge methodology and interdisciplinary applications
  • Skills training in presentation, scientific writing, funding applications and scientific leadership
  • Training plans will be developed holistically to benefit the scientific needs and interests, as well as the career goals of the individual.

Funding Information

The position is not currently funded and therefore the candidate will need to secure funding.

HOW TO APPLY

To apply for this research degree, please click here.