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Queen Mary University of London
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Fully Funded PhD in AI for Healthcare and Pregnancy Complications at Queen Mary University of London Queen Mary University of London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Aug 14, 2026
Country
United Kingdom
University
Queen Mary University of London

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About this position
Fully funded PhD studentship at Queen Mary University of London in AI for Healthcare, focused on prediction of miscarriage and pregnancy complications using Machine Learning and Artificial Intelligence. The project is hosted by the School of Engineering and Materials Science and uses NHS clinical data to develop AI and Natural Language Processing solutions for early prediction and improved maternal care.
Research themes include Artificial Intelligence, Machine Learning, Natural Language Processing, Clinical Data Science, Digital Health, Biomedical Engineering, Bioengineering, Health Informatics, and Women's Health. The successful candidate will work with clinicians, engineers, and data scientists from Queen Mary University of London, University College London Hospital (UCLH), and Manchester University NHS Foundation Trust.
This is a fully funded PhD studentship with an annual stipend of £22,618 (2026/27). The opportunity is based in London, United Kingdom.
Eligibility is aimed at medical graduates (MBBS or equivalent) who are undertaking Specialty Training (ST2–ST5), especially in Obstetrics & Gynaecology, Fetal Medicine, Emergency Medicine, General Practice, or related clinical specialties. The application deadline is 14 August 2026.
Apply via the linked Queen Mary portal and review the studentship reference SEMS-PHD-736 before submitting your application.
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
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