Research Fellow (Data Analysis)

Full-time: 35 hours per week 

Fixed-term: available from July 2026 for 12 months

Where discovery never stops. Be part of something bigger.

The University of Edinburgh is a world-class organisation. We are a large University covering a wide range of activities. In Professional Services, we support the University’s research and teaching, offering many career and role specialisms.

The Opportunity:

The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh is looking for a Research Fellow (Data Analysis).

This post offers the opportunity to work on an exciting new global collaborative initiative using wearable sensors and data driven research approaches to improve maternal and foetal outcomes during childbirth. You will join a collaborative research project entitled, ‘Intelligent Pregnancy Products Platform; I3P’ to provide near-real time analysis of continuous physiological data and clinical event data in a large scale, international, cluster-randomised trial.  You will work in a vibrant research environment collaborating with international stakeholders and industry partners to analyse the results of a trial of 13,400 women across 30 hospitals in 4 countries (India, Rwanda, Nigeria & Pakistan). The IMPALA 2 trial (https://www.globalsurgeryunit.org/impala/) will use novel techniques and wearable technologies to collect continuous vital signs from both the mother and baby during. You will develop, evaluate, and deploy generative AI methods to predict the onset of maternal and neonatal complications. This body of work has the potential to reduce maternal and foetal complications on a global scale.

Your skills and attributes for success:

• A good degree and higher degree in a scientific or numerate subject, or able to demonstrate relevant and equivalent recent experience. 
• Experience in using statistical programming for data analysis and machine learning/deep learning, using python or R.
• Experience in monitoring, analysing and dissemination of complex information.
• Experience developing, evaluating, or deploying generative AI methods, particularly in applied or clinical contexts
• Ability to work well within a multi-disciplinary team, including international and industry partners.

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