Research Fellow - Health Data Scientist

About us

UCL established the Institute of Health Informatics (IHI) in August 2014 in the Faculty of Population Health Sciences. The aim of IHI is to conduct high quality data-intensive research to improve health at local, national, and international levels. delivers one of the largest and most highly regarded teaching programmes in health informatics and health data science. It is home to one of four UKRI Centres for Doctoral Training in AI in Healthcare.

The Faculty of Population Health Sciences has established itself as UCL's largest research-based faculty, encompassing eight institutes. More information available atwww.ucl.ac.uk/population-health-sciences/.

About the role

Institute of Health Informatics is looking to appoint a Research Fellow - Health Data Scientist to join our welcoming and vibrant Institute. The Research Fellow - Health Data Scientist will join our expert project team to deliver an exciting project alongside our industry partner. The postholder will work with contemporary electronic health record data sources, including the UK Biobank, Genes and Health and Our Future Health, to create and evaluate novel methods for defining phenotyping algorithms, develop detailed data analysis plans and contribute to writing technical documentation and scientific reports.

The Research Fellow - Health Data Scientist will help plan and participate in regular meetings with the funder to provide expert advice on cutting edge methodology in data science and phenomics.

The post is full-time (36.5 hours per week) and the post is funded until 31 December 2026, further funding may become available.

For informal enquiries please contact Ana Torralbo at

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

About you

The Research Fellow - Health Data Scientist will hold at least a PhD in a related field (e.g. computer science, health informatics, bioinformatics) or have a similar level of experience in an academic and/or industrial setting, as well as excellent knowledge of the Python scientific programming stack and best practices for software development. The postholder will have outstanding knowledge and experience of manipulating and analysing large electronic health record datasets, practical knowledge of controlled clinical terminologies (e.g. ICD-10 and SNOMED CT) and will have experience working with relational databases and SQL for manipulating electronic health record and clinical data.

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at research assistant Grade 6B (salary £38,607 - £41,255 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

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.

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.

What we offer

We offer flexible working options, including part-time and job-sharing opportunities, wherever possible.
As well as the exciting opportunities this role presents, we also offer some great benefits, including:
• 41 days holiday (pro rata for part-time staff) (27 days annual leave,
• 8 bank holidays, and 6 closure days)
• Cycle to work scheme
• Season ticket loan
• On-site gym

Our commitment to Equality, Diversity and Inclusion

The Institute prides itself on operating in an all-inclusive environment irrespective of personal, physical, or social characteristics.

As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.

We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and women.

You can read more about our commitment to Equality, Diversity, and Inclusionhttps://www.ucl.ac.uk/equality-diversity-inclusion
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