Research Associate in Data Analytics

at  Kings College London

Job id: 087866. Salary: £43,205 to £46,732 per annum, including London Weighting Allowance.
Posted: 15 April 2024. Closing date: 29 April 2024.
Business unit: Faculty of Life Sciences & Medicine. Department: Department of Population Health Sciences.
Contact details: Dr. Mariam Molokhia. mariam.molokhia@kcl.ac.uk
Location: Guy’s Campus. Category: Research.
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Job description
The primary purpose of the post is to support work for our NIHR HSDR grant, “Improving kidney failure risk calculations in ethnically diverse populations”, involving epidemiological data analysis using electronic health records. This will include developing applications of epidemiology to translational medicine and public health. The post holder will contribute to risk prediction studies and research to develop methodologies and applications in ‘big data’ research using traditional statistical approaches and machine learning methods. You will undertake translational research to address health priorities for underserved and minority ethnic populations, aiming to reduce kidney health inequalities.
You will join a team that utilises large datasets derived from primary care electronic records, health services and public health research including CPRD and Lambeth DataNet.
You will contribute to both epidemiological studies of chronic kidney disease (CKD) and also to the work of the team by using electronic health records and translational applications. The research will utilise prognostic modelling techniques for stratification using phenotypic information derived from the electronic clinical records for large populations with long term conditions.
This post will be offered on an a fixed-term contract until 31st October 2025.
100% full time equivalent.
Key responsibilities
Improve the predictive performance of the KFRE (Kidney Failure Risk Equation) using linked UKRR data for KRT risk prediction and communication of risk of kidney failure in ethnically diverse populations
Undertake the electronic health record (EHR) and related analyses over a 6-month period, supervised by the PI and co-applicant using linked UK renal registry datasets from 5 regions in the UK
Identify common data variables for extraction and analyses code, ACR rates and KRT incident rates
Assess the statistical performance of the 4-variable KFRE in adults with CKD from Black, Asian and minority ethnic groups
Compare performance of existing eGFR calculations when used in KFRE to predict KRT risk in training and validation datasets
Determine what biomarkers or factors, other than ethnicity, improve risk prediction of KRT
Estimate the proportion of people with KRT that are undiagnosed from our community data
Develop an ethnicity adjusted KFRE risk calculator
Estimate misclassification to allow sensitivity analyses, and depending on the results of our work, we will consider combining different sets of results in a joint meta-analysis
Develop links with academics in King’s College London and across King’s Health Partners and through our collaborators that will strengthen and promote the development of the candidate’s research interest and output
Support the supervision and management of staff working on the project
Participate on new grant applications, research project development and research problem solving. There will be opportunities to develop new projects with junior and senior colleagues in which research design and delivery challenges will have to be overcome
Undertake ongoing training and learning as agreed with supervisors
Have a commitment to enhancing Equality & Diversity, as well as a commitment to the principles of the Athena SWAN Charter are essential
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

Essential criteria

• PhD in statistics, epidemiology, data science or health-related discipline*
• First degree in mathematics, statistics or health related discipline
• Master’s degree in statistics, epidemiology, data science or health-related discipline or equivalent experience
• Advanced knowledge of medical statistics and epidemiology
• Skilled in statistical programming for epidemiological data analysis e.g. knowledge of r/stata/other programming software
• Experience of writing for publication
• Committed to equality, diversity and inclusion, actively addressing areas of potential bias
• 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 criteria

• Expertise using electronic health records e.g. CPRD and similar
• Experience of applying for research funding
• Expertise in health research as applied to translational medicine
• Experience of undergraduate or postgraduate teaching
• Ability to contribute to supervision for analytical research

Further information
Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter.
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 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 five Departments.
More information: https://www.kcl.ac.uk/slcps

Please refer the Job description for details