Available
Project number:
2025_22
Start date:
October 2025
Project themes:
Main supervisor:
Clinical Senior Lecturer
Co-supervisor:
Michele Orini, Senior Lecturer in Healthcare Engineering, Dept Biomed Engineering, King's College London
Additional Information:
Combining maternal wearables and clinical data to detect abnormal fetal growth; a study in pregnant women
Background. Abnormal fetal growth, characterised by restricted growth or overgrowth affects more than 20,000
women in the UK every year, and can lead to significant neonatal and offspring complications, potentially
impacting health across the lifespan. There are multiple drivers of abnormal fetal growth but their interaction is
poorly defined.
This project will use unique data collected as part of an ongoing MRC-funded study (MR/W003740/1) currently
recruiting pregnant women (n=750). Study procedures include collection of maternal demographic, socioeconomic
and clinical data, dietary and physical activity questionnaires, multiple blood and urine samples, serial fetal
ultrasound and wearable devices collecting glucose levels and physical activity.
Version Date: August 2024
Novelty and Importance. This study is important because abnormal fetal growth is common and is associated with
life-long consequences, yet the interaction of the determinants is poorly understood. This PhD presents a novel
study design combining information from multiple data-streams, including wearable devices for simultaneous
measurements of blood glucose and physical activity, collected at different key stages of pregnancy. The
granularity of the dataset will facilitate careful analysis of the interaction of overlapping behaviours and risk
factors to elucidate the impact on fetal growth.
Aim. To develop a new computational approach integrating wearable, clinical and demographic data collected at
multiple time-points to elucidate pathways to abnormal fetal growth.
Objectives.(1) To understand determinants of fetal growth and birthweight by carrying out longitudinal profiling
in pregnant women of all contributing variables; (2) To develop a risk stratification model for early identification of
abnormal fetal growth risk in pregnancy.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at