Research Fellow in Epidemiology/Health Data Science

UCL Eastman Dental Institute
London
2 months ago
Applications closed

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About the role

Institute of Health Informatics is looking to appoint a full time ( hours per week) Research Fellow in Epidemiology / Health Data Science to join our welcoming and vibrant Institute.

This position presents a unique opportunity to join a team of experienced health data scientists, informaticians, statisticians and clinical epidemiologists and contribute significantly to the statistical analysis and subsequent presentation of results from large scale national and rich local health record data resources. The Research Fellow in Epidemiology / Health Data Science will analyse health data from 56 million people including coded data in Hospital Episode Statistics from the NHS England Secure Data Environment and primary care. They will develop reproducible analytic pipelines in one or more of the following: health care procedure data, geographic location data and/or temporal trends, and will design and execute analytic pipelines in our Atlas for Health.

A full range of duties can be found on the attached job description.

The post is funded until 31 December , further funding may become available.

Appointment at Grade 7 (£43, - £51, per annum) is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B (£38, - £41, per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

For an informal discussion please contact Professor Harry Hemingway at . 

For any queries regarding the recruitment process please contact Anita Gorasia at . 

About you

If you believe you meet the requirements why not come and be part of this unique and exciting opportunity and be part of something where you feel included, valued and proud.

The Research Fellow in Epidemiology / Health Data Science must have a PhD or appropriate equivalent experience in epidemiology, data science, biostatistics or related quantitative discipline as well excellent statistical analysis programming skills in R and/or R-Studio and the ability to meet deadlines and work effectively as part of an inter-disciplinary team. The role holder will have experience of wrangling large-scale, structured electronic health records and experience using disease ontologies and classifications (particularly International Classification of Didsease-10th revision), and experience developing reusable pipelines for managing and analysing large datasets (> million rows).

Please review the job description before applying, paying particular attention to the essential / desirable criteria, and ensure your experience in these areas is addressed in the questionnaire section of the application.

What we offer

We will consider applicates to work on a part-time, flexible and job share wherever possible.

As well as the exciting opportunities this role presents, we also offer some great benefits some of which are:, 41 Days holiday (pro rata for part time staff) (27 days annual leave 8 bank holiday and 6 closure days), cycle to work scheme, season ticket loan, on-site gym and employee assistance programme

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