Inkfish Principal Statistician and Methodological Lead in Digital Trials

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.

About the role

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.

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, starting in April 2025. 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. It is led by Professor Josip Car.

The post of Inkfish Principal Statistician and Methodological Lead in Digital Trials on the EMBRACE study represents an exceptional opportunity for an internationally recognised expert in statistics with a strong track record in methodological leadership in digital trials to contribute to a globally pioneering programme focused on maternal and early childhood health. The post holder will serve as the Principal Statistician and Methodological Lead in Digital Trials for the EMBRACE programme, providing strategic direction and scientific leadership across the design, analysis, and interpretation of both observational and interventional studies, with a particular emphasis on digital and AI-enabled trials. The post demands strong expertise in implementing methodological frameworks and in clinical epidemiology. A central responsibility will be to lead protocol design, develop methodological frameworks, and oversee statistical analyses, in alignment with regulatory, ethical, and governance frameworks relevant to digital health research and AI-enabled studies (e.g. GDPR, GCP, and AI ethics). The post holder will direct core methodological workstreams within the EMBRACE consortium, and collaborate closely with global partners in academia, healthcare, and industry to drive innovation and maximise translational impact.

The post holder is required to hold a PhD degree in statistics, biostatistics, epidemiology, health data science, or other closely related disciplines. They will bring internationally recognised expertise in statistics and methodological leadership in digital trials, demonstrated by a strong record of publications and contributions to the design and delivery of complex, large-scale clinical and population health studies. The post will directly lead and manage a team of Research Scientists, along with providing wider senior leadership and direction via matrix management within the study.

The post is an academic appointment at professorial level with the focus of the post holder’s time being on the EMBRACE programme. The post holder’s performance will be reviewed in the context of the Faculty of Life Sciences & Medicine’s academic performance framework for education and research academic appointments. The post holder is expected to be able to evidence academic achievement in the form of peer reviewed research papers, sustained research funding and a strong national and international profile for their work. Experience of working collaboratively, developing staff and students, creating a positive research culture is required, along with working collaboratively with international partners.

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

About You

To be successful in this role, we are looking for candidates to have the following skills and experience:

• PhD in statistics, biostatistics, epidemiology, health data science, or other closely related disciplines
• Proven internationally recognised leadership in the development and implementation of innovative statistical and methodological approaches, particularly in design and conduct of AI-enabled or digital trials within large-scale observational and interventional population health studies
• Extensive experience in clinical epidemiology, with a strong track record of applying epidemiological principles to real-world healthcare data and study design
• Strong publication record in high-quality peer‑reviewed journals, relevant to digital health, statistics, clinical trials, and epidemiology
• Success in securing substantial competitive research funding, with experience in leading or contributing to core methodological components of major grant proposals
• Familiarity with regulatory, ethical, and governance frameworks relevant to digital health research and AI-enabled studies (e.g. GDPR, GCP, and AI ethics)
• Excellent leadership, mentoring, and communication skills, with the ability to mentor diverse research teams and engage effectively across academic, clinical, and industry sectors
• Experience contributing to multi‑site or international collaborative research programmes, particularly in maternal, perinatal, or population health
• Experience applying machine learning or AI methods in healthcare research, particularly within digital trials or real‑world data studies
• Expertise in analysing complex digital health data, including wearable sensor data, mobile health survey, and electronic health records

Further Information

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.

As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. 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 advert. 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.

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 early February (TBC). This post is subject to Disclosure and Barring Service and Occupational Health clearances.