Research Associate in Medical Statistics & Stroke Epidemiology
We wish to appoint a Research Associate who will be a member of South London Stroke Register (SLSR) group at the School of Population Health & Environmental Sciences. The successful candidate will be the lead analyst for a series of innovative projects in stroke epidemiology for a new NIHR funded programme aimed at informing the care of stroke patients in the 2020s, based on the SLSR and related datasets.
The programme aims to improve the lives of stroke survivors by improved use of data, and is strongly multi-disciplinary, including collaboration with statisticians, computer scientists, social scientists, health economists, policy makers, and stroke survivors and their carers. We aim to improve patient care by allowing effective planning of services, personalised care, and reducing inequalities in access to care and outcomes after stroke. The post holder candidate will have expertise in epidemiological research and analytics, and lead and contribute to these aspects in the Programme.
This will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. Key research areas include the incidence of the new ICD-11 definition of stroke, trends over time in health outcomes including disability, cognitive function and mental health, phenotyping stroke subtype and multimorbidity, individual risk and recovery prediction, and population projection.
The postholder will have completed a PhD in a relevant discipline and have expertise in quantitative research methods. They will be someone who thrives in a highly collaborative and interdisciplinary environment, but is able to work independently, solve problems and deliver research to tight deadlines. The role will involve collaboration with experienced researchers across medical statistics, epidemiology, informatics, social science and health economics and integration into the broader SLSR team.
This is an outstanding opportunity to develop a research career through high quality publications, contributing to research proposals and taking advantage of developmental opportunities within the department and KCL.
King’s is committed to fostering an environment of equality, diversity and inclusion.
This post will be offered on an a fixed-term contract for 3 years with the possibility of an extension, subject to funding.
This is a full-time post – 100% full time equivalent
- Conduct epidemiological analysis (population incidence, survival analyses) of new ICD-11 SLSR data collection
- Apply advanced statistical and machine learning methods to model longitudinal trends in incidence and outcomes and derive patient phenotypes (multimorbidity, frailty, stroke subtype) from register data linked to health and administrative records
- Develop statistical tools (individual prediction, population projection) for integration into interactive patient and policy portals
- Prepare scientific/research data to be presented at internal and external meetings in relation to the programme of research
- Prepare and contribute to the preparation of manuscripts for publication in peer-reviewed journals
- Contribute to research proposals for further funding
- Contribute to the running of the SLSR project as appropriate to role and skill set.
- Ensure the success of a multidisciplinary research programme, contributing and leading the conduct of all epidemiology and analytics aspects
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
Skills, knowledge, and experience
- PhD in Medical Statistics or Epidemiology
- Experience working with large datasets
- Experience with relevant statistical software (R/Stata)
- Experience writing/contributing to manuscripts for publication
- Research experience in Public Health/Epidemiology/Informatics/ Statistics
- Excellent written and oral communication skills
- Ability to work in a multidisciplinary team and independently
- Committed to equality, diversity and inclusion, actively addressing areas of potential bias
- MSc in Statistics or Epidemiology
- Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data
- Publications in high impact journals
- Experience in stroke or cardiovascular disease research
Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter.
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*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.
The School of Population Health & Environmental Science’s research comprises Analytics (broadly defined as the discovery and interpretation of meaningful patterns in quantitative and qualitative data), Investigation (broadly exploring analytical solutions to complex problems at the individual as well as population level) and Applied Research (broadly using analytics, including laboratory investigations, to identify needs and propose and evaluate new solutions to global societal health and social problems). This informs our approach and focus to developing and conducting research that addresses major questions, such as long-term conditions, multimorbidity, and environmental impacts on population health.
This is an exciting time to join the Department and the School as we will soon merge with the existing School of Life Course Sciences. This will bring together very considerable clinical, scientific, and population/global health strengths. There are already many examples of joint working and collaboration between the two Schools, and it is envisaged that there will be significant opportunities to collaborate further and draw upon the critical mass of clinical, methodological, and applied researchers in the new, integrated School. The School will be one of the largest in the Faculty with strong links to the NIHR BRC and NIHR Applied Research Collaboration and with King’s Health Partners Clinical Academic Groups and Institutes, with the enormous potential to further leverage these synergies.
About the Faculty: https://www.kcl.ac.uk/lsm/index.aspx
About the School of Population Health and Environmental Sciences: www.kcl.ac.uk/sphes
About the Medical Statistics Unit: https://www.kcl.ac.uk/research/medical-statistics
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This post is subject to Disclosure and Barring Service and Occupational Health clearance.