Description du poste
Hidradenitis suppurativa, one of dermatology’s most painful conditions, affects around one in 130 UK residents, causing recurrent boils, abscesses and scarring in the armpits, groin and under the breasts. Oral antibiotics are a mainstay of treatment, often taken for months or years, but their impact on future antibiotic effectiveness is unknown. This PhD will answer that question using electronic health records. You will work with the Clinical Practice Research Datalink Aurum, linked to hospital admission and mortality data. You will: map how antibiotics are prescribed for hidradenitis suppurativa across the UK and how this has changed; use machine learning to uncover distinct patterns of treatment over time and test whether they predict disease flares; and estimate whether prolonged antibiotic exposure is followed by antibiotic treatment failure when patients are later treated for chest or urine infections. You will be trained in epidemiological study design, causal inference, survival analysis, machine learning and statistical programming, and in the governance of large health datasets. Supervision spans dermatology, pharmacoepidemiology and health informatics. You will join the Dermatology and Pharmaco-epidemiology Research Group in Manchester, within a dermatology centre that is a standalone theme of the NIHR Manchester Biomedical Research Centre. You will be supported to work with patients in shaping research. Antimicrobial resistance is a national priority, yet dermatology evidence is scarce. Findings aim to inform clinical guidelines and stewardship policy, with all analysis code shared openly. Entry Requirements Competition for studentships is expected to be very high. Applicants are expected to hold (or be about to obtain) a minimum upper second-class undergraduate honours degree (or equivalent) in medicine, pharmacy, epidemiology, public health, statistics, data science, health informatics or a related quantitative discipline. A relevant Masters degree is desirable. Research experience in health data analysis, and familiarity with a statistical programming language (R, Stata or Python), are desirable. Successful applicants may also have: A master's qualification. Relevant research experience. Experience demonstrating suitability for doctoral research. Applicants who are offered a place must meet the University's English language requirements before commencing studies. Further information can accessed here: English language requirements | International | The University of Manchester Application Guidance Candidates must contact the primary supervisor before applying to discuss their interest and assess suitability. Apply directly here: MRC North West Doctoral Programme in Medical Sciences | Biology, Medicine and Health | The University of Manchester or on the online application portal, select MRC NW-DMS PhD Programme as the programme of study. You can apply for up to two projects within this scheme and you must submit a separate application for each, including a supporting statement tailored to the specific project. Please ensure that your application includes: Curriculum Vitae (CV) Supporting Statement Academic Certificates and Transcripts Applicants must provide two references. References can be submitted shortly after the application deadline, but please provide them as soon as possible to avoid delays. Incomplete or late applications will not be considered. Further details: MRC North West Doctoral Programme in Medical Sciences | Biology, Medicine and Health | The University of Manchester Equality, diversity and inclusion are central to the University’s activities: Study | Biology, Medicine, Health | University of Manchester Funding These studentships offer UK and international applicants four years of full funding, covering tuition fees at their applicable fee status (including international fees) and a UKRI-rate stipend.