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The University of Manchester invites applications for a 4-year PhD studentship. Open to Home (UK) and international applicants, it offers an annual stipend at the UKRI minimum rate plus £1,000 enhancement, and a research training grant of up to £20,000 for the full programme.
The project investigates how menopause and hormonal changes influence urinary microbiology using mathematical modelling, microfluidic lab-on-a-chip experiments, and genomics. Start is anticipated in September 2027.
This4-yearPhDstudentshipisopentobothHome(UK)andinternationalapplicants.The successful candidate will receive an annual stipend at the UKRI minimum rate (currently £21,805 per year) plus £1,000/annum enhancement, and a research training support grant of up to £20,000 for the full 4-year programme. This project is in competition for funding with other projects. Usually, the projects that receives the best applicants will be successful.
WhydoesprevalenceofUTIsincreasesosubstantiallyduringthemenopause?Howdothehormonalchangesassociatedwithmenopausecometoaffectcompetitionbetweenbacterialspeciesintheuniqueflowconditionsofthebladderandurethra?We hypothesise that menopause-associated changes in hormone signalling alter the urinary tract environment, disrupting the balance of microbial communities and their interactions with the host.
We will use an interdisciplinary approach, combining mathematical modelling, microfluidic lab-on-a-chip experiments with cells, and bioinformatics and genomics to study how cell signalling affects gene expression.In particular, we want to capture how microbial competition is communicated -how cells sense and respond to biochemical and mechanical signals from the same and other microbial species and those from the host environment.Afurthergoalistounderstandourroleasscientistsandsensors:howshouldmicrofluidicdevicesbestbedesignedanddeployedassensorsandemulatorsofdisease?
For further details see here.
ThisprojectisexpectedtostartinSeptember2027.
Applicants are expected to hold (or be about to obtain) a minimum upper second-class undergraduate honours degree (or equivalent) in applied mathematics, physics, engineering or biology. Research experience in mathematical modelling and/or biology is desirable.