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School of Engineering and Materials Science Research Studentships

Machine leaning models to predict the risk of preterm birth

Supervisors: Tina CHOWDHURY

Application Deadline: 30-01-2022

The integrity of the fetal membranes that surrounds the baby in the womb during pregnancy is vital for normal development. Once the fetal membranes have ruptured or are damaged, they fail to heal leaving a defect until the end of pregnancy. This condition is called pre-term premature rupture of the fetal membranes (PPROM). Exposure to air pollution during pregnancy is associated with PPROM leading to preterm birth. Air pollution results mainly from the combustion of fossil fuels and from industrial emissions and has become a major global public health issue for all people in all age groups. In England, PPROM affects 1 in 9 pregnancies and in London, this increases to 1 in 7 annually. Unicef Executive Director warned the dangers of air pollution to unborn babies. Environmental harm during gestation, infancy and early childhood will have long term impacts across the lifetime. Currently, there are no clinical solutions to improve healing of the fetal membranes after they rupture.

You will :

  • Cross-validate experimental data from placenta and fetal cell populations (cell mechanics, collagen, inflammatory biomarkers) with computational models to predict the risk of membrane failure to pollution.
  • Develop a biomarker database of individual characteristics linking clinical data from women (maternal and umbilical cord blood, amniotic fluid, intact placenta) with risk factors taken from women’s demographics (gestational age, BMI, postcode location, work/home lifestyle, causes of PPROM).
  • Use experimental and clinical data to learn relationships and build machine learning tools that will automate analysis and predict women who are at greater risk of PPROM and preterm birth.
  • You will work with a multi-disciplinary team of data engineers, scientists and clinicians from QMUL (Prof Jonathan Grigg), DERI (Prof Greg Slabaugh), UCL/UCLH (Prof Anna David).
  • You will help to raise awareness of our campaign to #SaveBabiesLives and prevent PPROM with Little Heartbeats and UCLH Prenatal Charity.

Key skills needed for the PhD project

  • Collaborative and multi-disciplinary
  • Background for example in biomechanics, mechanobiology, modelling, AI and healthcare
  • The candidate must have a strong interest in clinical and environmental regenerative medicine and artificial intelligence.

Interviews will follow a two-step process where you will 1. present your research to date and 2. show how your skills align with the proposed work.

More about our research


This studentship is fully funded via the UKRI EPSRC Doctoral Training Programme for 3.5 years and includes a stipend (currently £17,609 in 2021/2022) and Fees.


This year UKRI announced that there will be a limited number of studentships for international students available.  International applicants are encouraged to apply but should note that studentship awards will be subject to eligibility and the availability of funding.

To be classed as a home student, applicants must meet the following criteria:

  • Be a UK National (meeting residency requirements), or
  • Have settled status, or
  • Have pre-settled status (meeting residency requirements), or  
  • Have indefinite leave to remain or enter

If a candidate does not meet the criteria above, they would be classified as an international student.

Further guidance on UKRI Eligibility Criteria is here, and within Annex One of the International Eligibility Guidance.

  • The minimum requirement for this studentship opportunity is a good Honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking).
  • Candidates are expected to start from September 2022

Supervisor Contact Details:

For informal enquiries about this position, please contact Dr Tina Chowdhury, E-mail:

Application Method:

To apply for this studentship and for entry on to the PhD Full-time Medical Engineering - Semester 1 (September Start) please follow the instructions detailed on the following webpage:

Research degrees in Engineering:‚Äč

Further Guidance:

Please be sure to include a reference to ‘2022 EPSRC DTP TC’ to associate your application with this studentship opportunity.