GOSH BRC Applied Child Health Informatics Theme (Non-Clinical) PhD Studentships

An exciting non-clinical PhD opportunity at the NIHR Great Ormond Street Hospital Biomedical Research Centre (NIHR GOSH BRC) is open for applications. The NIHR GOSH BRC Applied Child Health and Informatics (ACHI) PhD Studentship Programme aims to fund two highly motivated non-clinical Health Data Science PhD studentships to support the training and development of the next generation of informatics and data science translational researchers. The full-time studentships will begin on 1 October 2024 and be based at Great Ormond Street Hospital (GOSH) and the UCL Great Ormond Street Institute of Child Health (ICH). The studentship offers a starting stipend of £21,181 per annum (includes London weighting) as well as the cost of tuition fees for UK students, and £5,000 contribution towards the running costs of their project. We will support two students, one in the area of health data science/epidemiology/statistics and the other specialising in applied machine learning and informatics.

The closing date for submission of applications is Wednesday 15 May 2024. Please see our webpage for more details and how to apply: NIHR GOSH BRC Applied Child Health Informatics Theme (Non-Clinical) PhD Studentships 2024

The NIHR Great Ormond Street Hospital Biomedical Research Centre (NIHR GOSH BRC) is a collaboration between Great Ormond Street Hospital (GOSH) and the UCL Great Ormond Street Institute of Child Health (ICH). The NIHR GOSH BRC provides cutting-edge facilities and world-leading expertise and access to over 200 rare disease patient populations allowing our staff and NHS, university and industry collaborators to conduct pioneering translational research into childhood illnesses.

Prospective PhD students are required to apply to a specific project, with students selecting a first and second choice project (in priority order).The list below provides a summary of the projects available, further details about each of the projects can be found on our website.

Project number / Project Title / PhD Supervisory Team

Health Data Science/Epidemiology/Statistics:

1: Health and development outcomes and their interaction for children with chronic liver disease: a population-based cohort using novel linkage between health and education records:

• Prof Katie Harron, UCL Great Ormond Street Institute of Child Health (primary)
• Dr Ania Zylbersztejn, UCL Great Ormond Street Institute of Child Health (subsidiary)
• Dr Marianne Samyn, King’s College Hospital NHS Foundation Trust (subsidiary)

2: Health outcomes of children with rare or complex conditions and their families: a longitudinal cohort study using linked primary and secondary healthcare data in England:

• Dr Ania Zylbersztejn, UCL Great Ormond Street Institute of Child Health
• Dr Joachim Tan, UCL Great Ormond Street Institute of Child Health
• Prof Mario Cortina-Borja, UCL Great Ormond Street Institute of Child Health

3: Harms to children and young people in the UK due to health service delays in management of eye/vision conditions:

• Prof Jugnoo Rahi, UCL Great Ormond Street Institute of Child Health (primary)
• Dr Ameenat Lola Solebo, UCL Great Ormond Street Institute of Child Health (subsidiary)

4: Health and education outcomes of children with Sickle Cell Disease in England:

• Dr Rachel Knowles, UCL Great Ormond Street Institute of Child Health (primary)
• Prof Pia Hardelid, UCL Great Ormond Street Institute of Child Health (subsidiary)

5: Developing statistical approaches to analyse and report reinterventions in children who have heart surgery for national benchmarking and quality improvement:

• Dr Deborah Ridout, UCL Great Ormond Street Institute of Child Health (primary)
• Prof Katherine Brown, Great Ormond Street Hospital (subsidiary)

Applied Machine Learning and Informatics:

6: Disease modelling to understand long-term progression and treatment response in Spinal Muscular Atrophy and Duchenne Muscular Dystrophy:

• Prof Giovanni Baranello, UCL Great Ormond Street Institute of Child Health (primary)
• Dr Deborah Ridout, UCL Great Ormond Street Institute of Child Health (subsidiary)

7: Using artificial intelligence and machine learning techniques to improve diagnosis and predict outcomes in children with heart muscle disease:

• Prof Juan Pablo Kaski, Great Ormond Street Hospital
• Dr Gabrielle Norrish, Great Ormond Street Hospital

8: Precision Diagnosis for Congenital Anomalies – using AI & leveraging multimodality data to help counsel parents appropriately in rare diseases:

• Dr Susan Shelmerdine, Great Ormond Street Hospital
• Prof Ivana Drobnjak, UCL Dept of Computer Science
• Prof Owen Arthurs, UCL Great Ormond Street Institute of Child Health

9: Multimodal Artificial Intelligence for the Detection and stratification of Necrotising Enterocolitis in premature born infants (MAIDNEC):

• Prof Simon Eaton, UCL Great Ormond Street Institute of Child Health (primary)
• Dr Evangelos Mazomenos, UCL  Dept of Med Phys & Biomedical Eng (subsidiary)

10: Using big data to better define disease types and predict outcome in childhood myositis:

• Prof Lucy R Wedderburn, UCL Great Ormond Street Institute of Child Health
• Prof Mario Cortina-Borja, UCL Great Ormond Street Institute of Child Health
• Dr Merry Wilkinson, UCL Great Ormond Street Institute of Child Health

11: AIDE: an Artificial Intelligence aiDed clinical support system on Edge for emergency transport of critically ill children

• Prof Mark Peters, UCL Great Ormond Street Institute of Child Health (primary)
• Dr Kezhi (Ken) Li, UCL Institute of Health Informatics (subsidiary)
• Dr Philip Knight, Great Ormond Street Hospital (subsidiary)

Applicants should have or expect to receive a first class or upper second-class degree in a relevant discipline or an overseas qualification of an equivalent standard. Please note, this studentship covers the cost of tuition fees based on the UK (Home) rate. Non-UK students are welcome to apply, but will have to fund the difference between the UK (Home) rate and the overseas rate where they are not eligible for UK fee status.

To apply, prospective PhD students will need to submit an application form which can be found on our website, along with a CV and arrange for two references to be sent to brc@gosh.nhs.uk via the ‘Apply’ button above. The deadline for applications is Wednesday 15 May 2024. Following submission of applications, there will be several stages to the process of selecting students, including interviews due to take place in June.

NIHR GOSH BRC ACHI PhD studentship guidance and application form

Please contact brc@gosh.nhs.uk if you have any questions.