Research Associate in Deep Learning and Fetal Neurosonography

An exciting opportunity has arisen for a talented postdoctoral researcher to join the Oxford Machine Learning in Neuroimaging (OMNI) lab, led by Professor Ana Namburete, in collaboration with the internationally renowned INTERGROWTH-21st Consortium. This role involves developing advanced deep learning techniques to identify early indicators of fetal vulnerability using clinically-acquired ultrasound (US) images, specifically exploring at-risk fetal populations from the comprehensive INTERBIO-21st dataset. Ultrasound imaging is the cornerstone of pregnancy care globally. The OMNI lab has developed specialised machine learning tools for automated segmentation and volumetric analysis of fetal brain structures from ultrasound scans (NeuroImage 2022; 254:119117; NeuroImage 2022; 258:119341). Building upon this foundation, the post-holder's research will leverage the INTERBIO-21st dataset, which contains serial ultrasound scans of 3,598 fetuses developing under sub-optimal conditions (such as maternal HIV, malaria, and malnutrition) across low-, middle-, and high-income settings. The candidate will conduct rigorous statistical comparisons between this high-risk cohort and healthy benchmarks provided by the normative atlases from the INTERGROWTH-21st Project (Nature 2023; 623:106). This represents one of the first detailed investigations of in utero cortical development under such diverse conditions. Additionally, the INTERBIO-21st dataset (Nature Medicine 2021; 27:647) includes comprehensive maternal and perinatal health data, longitudinal neurodevelopmental outcomes at 2 years of age, and genetic, epigenetic, metabolomic and proteomic data, providing a unique opportunity for multidimensional correlation studies on early brain development. The post-holder will join an interdisciplinary team renowned for expertise in AI-driven fetal brain imaging, clinical obstetrics, pregnancy physiology, and global health technology innovation, particularly aimed at low- and middle-income countries (LMICs). The primary location will be the Department of Computer Science at Oxford, with additional supervision from Professor Stephen Kennedy at the Nuffield Department for Women's and Reproductive Health, John Radcliffe Hospital. The successful applicant will report to the project PI, Professor Ana Namburete. The position is available immediately. Flexible working This is a full-time role (37.5 hours per week) that requires on-site working. Some flexibility may be possible, depending on work needs, such as attending in-person meetings or travelling for conferences. What We Offer As an employer, we genuinely care about our employees' wellbeing and this is reflected in the range of benefits that we offer including:

• An excellent contributory pension scheme
• 38 days annual leave (pro-rata for part-time roles)
• A comprehensive range of childcare services
• Family leave schemes
• Cycle loan scheme
• Discounted bus travel and Season Ticket travel loans
• Membership to a variety of social and sports clubs