S.E. Seaton
3 months ago
Exploring Care Pathways in Children with Respiratory Disease Prior to Critical Care Admission: A Data-Driven Approach University of Leicester in United Kingdom
Degree Level
PhD
Field of study
Public Health
Funding
Funded PhD Project (Students Worldwide)
Deadline
Expired
Country
United Kingdom
University
University of Leicester

How do Bangladeshi students apply for this?
Sign in for free to reveal details, requirements, and source links.
Where to contact
Official Email
Keywords
About this position
This PhD project, based at the University of Leicester's Department of Population Health Sciences, investigates the healthcare pathways of children with respiratory disease prior to admission to paediatric intensive care units (PICUs) in the UK and Ireland. Each year, approximately 18,500 children are admitted to PICUs, with many emergency cases linked to respiratory conditions such as bronchiolitis. Despite frequent healthcare interactions before PICU admission, the trajectories and risk factors leading to critical care remain poorly understood.
The research will leverage large-scale linked datasets, including the Clinical Practice Research Datalink, Hospital Episode Statistics, and the Paediatric Intensive Care Audit Network, to map and analyze patterns of GP visits, emergency department attendances, and hospital admissions preceding PICU entry. Advanced statistical techniques, such as multistate modelling and sequence analysis, will be employed to identify key pathways and risk factors associated with PICU admission. The project will also address health inequalities, examining differences in access and outcomes by ethnicity and socioeconomic status.
Supervision is provided by Dr S.E. Seaton (lead), Dr David Lo (Respiratory Sciences, University of Leicester), and Prof Laila J Tata (Lifespan and Population Health Unit, University of Nottingham), offering expertise in child health, respiratory disease, and population health research. The student will benefit from collaborative support across two leading UK institutions.
Funding is available through UKRI competition funding, which includes a four-year stipend at UKRI rates, four years of UK tuition fees, and a full overseas fee waiver for one international applicant. The University of Leicester also offers full overseas fee waivers for all international students accepted at Leicester, with up to 30% of studentships available to overseas applicants. Additional support includes a research training support grant (RTSG) and a budget for purchasing a laptop.
This opportunity is ideal for candidates with strong quantitative skills and a keen interest in child health, medical statistics, and epidemiology. Applicants should have a relevant degree and experience in statistical analysis and handling large datasets. The findings from this research will inform earlier interventions and improved recognition of deterioration in paediatric care, contributing to safer and more equitable healthcare for children.
The application deadline is January 9, 2026. For further details and to apply, visit the MRC AIM PhD opportunities page. Project enquiries can be directed to Dr S.E. Seaton at [email protected], and programme enquiries to [email protected].
Funding details
Funded PhD Project (Students Worldwide)
What's required
Applicants should have strong quantitative skills and an interest in child health. A degree in a relevant discipline such as medical science, statistics, epidemiology, or data science is preferred. Experience with statistical analysis and handling large datasets is advantageous. No specific GPA or language test requirements are mentioned, but international students are eligible and encouraged to apply.
How to apply
Visit https://more.bham.ac.uk/mrc-aim/phd-opportunities/ for application instructions. Direct project enquiries to [email protected]. Programme enquiries can be sent to [email protected]. Prepare your application materials and submit before the deadline.
Ask ApplyKite AI
Professors

How do Bangladeshi students apply for this?
Sign in for free to reveal details, requirements, and source links.