Job description

We wish to appoint a Research Assistant or Research Associate who will be a member of South London Stroke Register (SLSR) group within the School of Life Course and Population Sciences. SLSR is one of the largest and longest running registries of stroke patients internationally, with >7000 patients registered since 1995 and over 20 years follow up. 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 (Oxford Vascular Study, Sentinel Stroke National Audit Programme).  

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 MSc (Research Assistant) or PhD (Research Associate) 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.

This is an outstanding opportunity to further develop skills and expertise in health data science in a priority area for health research and build 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 from 1st July 2022 to 30th June 2025 with the possibility of an extension, subject to funding. 

This is a full-time post – 100% full time equivalent

Key responsibilities

• 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 

Research Assistant  

Essential criteria 

•        First degree in mathematics/biostatistics or MSc with high biostatistics content

•        Experience working with large datasets 

•        Experience with relevant statistical software (R/Stata) 

•        Research experience in Public Health/Epidemiology/Statistics 

•        Ability to work in a multidisciplinary team and independently 

•        Committed to equality, diversity and inclusion, actively addressing areas of potential bias 

Desirable criteria 

•        MSc in Statistics or Epidemiology 

•        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.

Research Associate 

Essential criteria 

•        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/Statistics 

•        Ability to work in a multidisciplinary team and independently 

•        Committed to equality, diversity and inclusion, actively addressing areas of potential bias 

Desirable criteria 

•        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.

Further information

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, diabetes, 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 2014 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 six Departments  

About the Faculty:   https://www.kcl.ac.uk/lsm/index.aspx

About the Medical Statistics Unit:   https://www.kcl.ac.uk/research/medical-statistics