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Job id: 139028. Salary: £53,947 - £63,350 per annum, including London Weighting Allowance.

Posted: 20 February 2026. Closing date: 15 March 2026.

Business unit: Faculty of Life Sciences & Medicine. Department: Department of Population Health Sciences.

Contact details: Prof. Abdel Douiri. Abdel.douiri@kcl.ac.uk

Location: Guy's Campus. Category: Research.

About Us

The School of Life Course & Population Sciences is one of five 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

The Research Fellow in Translational and Digital Health Statistics is part of the Unit for Medical Statistics (UMS) within the School of Life Course & Population Sciences. It supports the increasing demand for advanced statistical expertise in clinical trials, including first-in-human studies, trials involving digital health technologies, real-world data analyses, and translational research.

The post holder works as part of a team, with day-to-day responsibility for the statistical components of clinical trials and related studies, including projects involving artificial intelligence and clinical trial methodology.

Key responsibilities include contributing to study design, data management strategies, analytical approaches, and inferential analyses for observational and translational research using real-world data. The post holder will work with large healthcare datasets, electronic health records, and registry data, while engaging with clinical and data science teams to represent statistical, epidemiological, and data science perspectives.

The postholder will hold a PhD in Medical Statistics/Biostatistics, Mathematics, Computer Science, Epidemiology, or another quantitative discipline, and will have strong programming skills, attention to detail, and experience with complex healthcare data.

This is a full time post (35 hours per week), and you will be offered a fixed term contract until 2nd March 2028.

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 You

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

Essential criteria

  1. PhD qualified in mathematics/biostatistics (or equivalent quantitative discipline) and relevant postdoctoral experience 
  2. Knowledge and experience of various statistical packages such as R, Stata, Python
  3. Experience with large healthcare datasets or administrative data
  4. Understanding of observational study designs and causal inference methods
  5. Knowledge of health research methodologies and current issues in real-world data analysis
  6. Be capable of working independently and collaboratively in a multidisciplinary team
  7. Track record of publication in clinical trials or trial methodology and contributing to grant funding applications 

Desirable criteria

  1. Experience analysing NHS data (HES, CPRD) or hospital electronic health records 
  2. Experience with data linkage and working with routine healthcare data 
  3. Experience with machine learning or AI applications in healthcare settings 
  4. Advisory or consultancy experience 
  5. Understanding of implementation research or health inequalities 

Downloading a copy of our Job Description

Full 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 Information

At 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.

To find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages.