NHS Innovation Placement: The movement of Data and Research across the clinical – academic boundary: how permeable is it?

In collaboration with Professor Ingrid Wolfe and her colleagues at the Evelina Children’s Hospital and the KCL Department of Women and Young People’s Health, DiRAC is pleased to invite applications for a 6-month Innovation Placement focusing on mapping the flow of data across research, clinical and decision-making boundaries.

Proposed start date: April/May 2026.

Applications are now closed.

Research Context

Evelina Children’s Hospital and the KCL Department of Women and Young People’s Health

Professor Ingrid Wolfe and her colleagues at the Evelina Children’s Hospital and the KCL Department of Women and Young People’s Health are building on their world-leading healthcare data research. This research contains some of the most complete and comprehensive longitudinal patient data in the world, in particular its collection of physical health and symptom status, mental health and wellbeing, and socio-economic data which complements the healthcare data.

As a host organisation, Evelina Children’s Hospital and the KCL Department of Women and Young People’s Health is able to provide:

Access to some of the most complete and comprehensive longitudinal patient data in the world.
A collection of physical health and symptom status, mental health and wellbeing, and socio-economic data which complements the health care data.
Work closely with the clinicians and healthcare professionals who write the notes, order tests and prescribe medicines and courses of treatment in order to construct the databases, what analysis and modelling/visualisation is needed, and to understand what constitutes an alert and what feedback is actually required and in what form.
Ability to work with prominent clinical leads, clinical academics and healthcare data specialists.

Placement Details

Location: London
Proposed start: April/May 2026.

We are pleased to offer a 6-month placement with Professor Ingrid Wolfe and her colleagues at the Evelina Children’s Hospital and the KCL Department of Women and Young People’s Health. This placement will provide hands-on experience in environments where data quality and flow are central to clinical decision-making. The placement will help to identify the analytical capacity to deal with data quality and integration to guide strategy on population health that is grounded on data quality and data evidence.

Applicant Profile, Skills & Experience

We value these 4 characteristics in Data Scientists and any successful applicant will demonstrate these capabilities:

Self-Starter – Takes independent action to identify and solve problems. Seeks out relevant information needed to make decisions. Gets involved with new initiatives.
Success/Achievement Orientation – Delivers quality results consistently. Targets, achieves (or exceeds) measurable results. Sets challenging goals, focuses on critical priorities, and is accountable.
Problem Solving – Recognises problems and responds with a systematic assessment that identifies and addresses the cause of issue. Practical, realistic, and resourceful.
Innovative – Builds and improves processes. Generates new ideas and solves problems creatively.

Responsibilities

Self-Starter – Takes independent action to identify and solve problems. Seeks out relevant information needed to make decisions. Gets involved with new initiatives.
Success/Achievement Orientation – Delivers quality results consistently. Targets, achieves (or exceeds) measurable results. Sets challenging goals, focuses on critical priorities, and is accountable.
Problem Solving – Recognizes problems and responds with a systematic assessment that identifies and addresses the cause of issue. Practical, realistic, and resourceful.
Innovative – Builds and improves processes that enhance the effectiveness of DDN. Generates new ideas and solves problems creatively.

Final Digital Asset

The primary digital asset is to identify the analytical capacity to deal with data quality and integration to guide strategy on population health that is grounded on data quality and data evidence.

equal opportunity

The NHS welcomes applications from all. All applicants will receive consideration without regard to race, national origin, gender, age, religion, disability, or any other category protected by law.

how to apply

Applications are now closed

Placement Details

Placements are fully funded but you must get your supervisor or PI’s permission before applying – under UKRI rules participation in the scheme is only allowed with their consent.

The successful candidate will remain based at their home university. We do our best to offer flexibility; part-time working can be arranged as long as the placement does not exceed 1 year.

If you have any questions, please email them to DiRAC_placements@leicester.ac.uk