Inkfish Research Scientist in Machine Learning for Wearables

About Us

The School of Life Course & Population Sciences is one of six Schools that make up the Faculty of Life Sciences & Medicine at King’s College London. The School unites over 400 experts in women and children’s health, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating life, disease and healthcare as a continuum. We are interdisciplinary by nature and this innovative approach works: 91 per cent of our research submitted to the Subjects Allied to Medicine (Pharmacy, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments.

King’s College London is an internationally renowned university delivering exceptional education and world-leading research. We are dedicated to driving positive and sustainable change in society and realising our vision of making the world a better place. We are delighted to announce exciting new opportunities to join our community.   

EMBRACE is a visionary, multicomponent International research programme, the first of its kind in the world, supported by Inkfish with £35M core funds over six years. It is a global study of 60,000 participants, including 20,000 mothers, 20,000 infants and up to 20,000 partners. It brings together world-leading clinician scientists across six distinguished Healthcare organisations, world-leading AI & technology companies, together with premier biotech companies, with the overarching aim to fast-track major scientific breakthroughs, revolutionise maternal and early childhood health through precision-personalised interventions, powered by a groundbreaking symbiosis of cutting-edge AI combined with human support.

About the role

The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner health and behaviour throughout pregnancy, enabling a holistic understanding of health trajectories and personalised interventions. The post focuses on analysing multimodal data collected from wearable devices (e.g., heart rate, sleep patterns, physical activity) and voice biomarkers to identify patterns linked to maternal health outcomes. The goal is to support personalised health interventions and contribute to the advancement of precision maternal and early childhood care within the EMBRACE research programme, which is led by Professor Josip Car. 

Multimodal wearable data will be collected from smartwatches/fitness trackers via continuously monitoring physiological metrics, including heart rate, heart rate variability, sleep patterns, physical activity levels, energy expenditure and so forth. They will be analysed to detect patterns and anomalies correlating with known markers of maternal health, including blood pressure, blood glucose, gestational weight gain, sleep and stress levels. In addition, the project will also aim to analyse voice biomarkers to capture unique vocal features that may reflect pregnant women’s physical and mental health risks and conditions. There will also be opportunities to develop research profile, travel for conferences and presentations, as well as contribute to academic publications.

The post holder is expected to hold a PhD degree in Bioinformatics, Computer Science or other relevant discipline. They will have skills in deep learning for wearable data analysis. Experience of studying health data science and/or machine learning for healthcare would be beneficial.

This is a full time post (35 hours per week), and a fixed term contract until 31/08/2029.

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