Research Associate/Fellow in Placenta and Maternal Health Data Science (Fixed Term)

We are seeking a highly motivated Research Associate/Fellow to join a multidisciplinary team developing advanced MRI and sensor data analytics methods to improve our understanding of placental function and reduce the risk of stillbirth. This post forms part of the internationally funded Wellcome Trust programme, which aims to develop new approaches to measure, model and predict pregnancy health using state-of-the-art imaging, sensors, computational modelling and data science.

The successful candidate will play a leading role in developing and implementing computational pipelines for MRI, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi-site datasets collected across international collaborators. The role will involve working closely with MRI physicists, clinicians, computer scientists, engineers and mathematicians to ensure high-quality, reproducible research that supports the development of new biomarkers for placental health.

You will join a highly collaborative, multidisciplinary research environment bringing together expertise in MRI physics, obstetrics, placental biology, biomedical engineering, mathematics, computer science and artificial intelligence. The team includes researchers from the University of Nottingham, Nottingham Trent University and international collaborators working together to improve the understanding of pregnancy and placental function.

About you:
• A PhD (or close to completion) in medical imaging, computer science, physics, data science or a closely related discipline.
• Experience in MRI image analysis and scientific programming, preferably using Python and modern computational libraries.
• Experience applying machine learning or artificial intelligence to biomedical data.
• Experience managing large research datasets, databases and implementing FAIR research data management principles.
• Excellent communication and collaborative skills, with the ability to work effectively within multidisciplinary and international research teams.

What we offer:
• A friendly, diverse, and supportive working environment.
• A hybrid working arrangement with the blended approach of home and office working each week.
• Generous holiday entitlement of 30 days (or pro rata) plus standard bank holidays and five university closure days including closure between Christmas and New Year.
• Our reward scheme grants bonuses of numerous values for excellent work.
• We are committed to staff development through the provision of training, continued support, and career progression opportunities.
• You will have access to a range of benefits and rewards, including fitness and health facilities, staff discounts, travel schemes and many more.

This role is full time (36.25 hours), fixed term for 1 year.