Research Scientist in Machine Learning for Wearables
Department : AI & Personalised HealthAbout UsKing’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 roleThe 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 you will be offered an a fixed term contract until 06/09/2029.Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information.About YouTo be successful in this role, we are looking for candidates to have the following skills and experience:Essential criteriaPhD in Bioinformatics, Computer Science or other closely related disciplineExperience in deep learning with a focus on predictive modelling for healthcare applications using wearable data (e.g., physical activity, heart rate, heart rate variability, sleep patterns)Sufficient breadth or depth of specialist knowledge in the discipline and of research methods and techniques to work within established research programmesProficiency in signal processing and anomaly detection techniques to interpret physiological and behavioural dataResearch skills, as evidenced by a track record in high-quality academic journal publications and/or contributions to scientific conferencesGood interpersonal skills, with evidence of networking across teams and complex organisation, along with external partnersAbility to write research reports and papers accessible to both academic and lay audiencesProject management skills - ability to initiate, plan, organise, implement and deliver programmes of work to tight deadlines* Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.Desirable criteriaKnowledge of maternal health indicators, such as blood pressure, blood glucose, gestational weight gain, and stress assessmentAbility or potential to contribute to the development of funding proposals in order to generate external funding to support research projectsDownloading a copy of our Job DescriptionFull details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process.Further InformationAt King’s, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great strengths of the university. The Equality Act of 2010 protects the rights of our students and staff and provides a framework to fulfil our duties to eliminate unlawful discrimination, harassment and victimisation and in addition, to advance equality of opportunity and foster good relations between those who share a protected characteristic and those who do not. At times, this will include balancing rights and beliefs that can feel in tension.We are committed to free speech and to academic freedom, believing that our foundational purpose as a university, is to create spaces where a wide range of ideas, including ideas that are controversial, can be discussed and debated, and where members of our community can express lawful views without fear of intimidation, harassment or discrimination.When engaging in the robust exchange of ideas, we ask that our community is mindful of our Dignity at King’s guidance.We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.We reserve the right to close adverts early due to the volume of applications we receive. While the closing date may change, all adverts will close at 23:59 to allow sufficient time for applications to be submitted on that day.We encourage you to apply at the earliest opportunity to avoid disappointment as once we have closed a vacancy you will be unable to submit your application.Artificial intelligence (AI) is evolving rapidly, and we recognise its growing role in professional work. Applicants may use AI tools to support preparation of their application, for example to research the role or structure written responses. However, applications must reflect the applicant’s own work and experience. AI tools should not be used during interviews or assessment activities unless this has been agreed in advance as a reasonable adjustment. Further guidance on the use of AI in recruitment can be found here.To find out how our managers will review your application, please take a look at our ‘ How we Recruit’ pages.Interviews are due to be held in SeptemberThis post is subject to Disclosure and Barring Service and Occupational Health clearances.Grade and Salary : £45,031 - £52,514 per annum, including London Weighting AllowanceJob ID : 154785Post Date : 07-Aug-2026Close Date : 06-Sep-2026Contact Person : Professor Josip CarContact Details : josip.car@kcl.ac.uk
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