Up to 30% off — ends 2 Aug
ONLY00h00m00s
Up to 30% off — ends 2 Aug
ONLY00h00m00s
Sarah Moxon
Just Landed
New Today
NIHR Maternity Disparities Consortium
Fully Funded PhD Studentship in Newborn Health, Implementation Science, and Data Science at LSHTM London School of Hygiene and Tropical Medicine in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableCountry
United Kingdom
University
London School of Hygiene & Tropical Medicine

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested scholarships
About this position
Exciting fully funded PhD studentship at the London School of Hygiene and Tropical Medicine (LSHTM) through the NIHR Maternity Disparities Consortium.
The project is titled “Methodology PhD Studentship – Developing approaches to identify, prioritise and evaluate enhanced care pathways for at-risk newborn populations (Code: T3-2)”. It focuses on newborn health, health inequalities, implementation science, data science, and health services research, with an emphasis on improving hospital-to-home care pathways for at-risk newborns and families.
The successful candidate will work with Primary supervisor Sarah Moxon and join a collaborative environment involving academic, clinical, and community partners, including NHS partners and people with lived experience. The studentship offers opportunities to build skills in routine data analysis, evidence synthesis, stakeholder engagement, and co-design, while contributing evidence that can inform policy and improve outcomes for newborns and families.
This is a doctoral opportunity for candidates interested in interdisciplinary research on neonatal and early-life care pathways, especially those motivated by reducing disparities and improving care for vulnerable populations. The post also notes that other PhD opportunities are available across the Consortium on related topics and methodologies.
Application details and eligibility criteria are available via the linked call. No deadline is stated in the post.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
Ask ApplyKite AI
Professors

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