In collaboration with 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 improving health outcomes for children and young people using data science and AI.
Proposed start date: January 2025
Applications are now closed.
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.
Location: London
Typical areas of improvement could be for direct patient care and population health management, with the aim of improving outcomes, reducing inequalities, and enhancing the efficiency of health system function.
As a student or early-career researcher, you will gain experience by being embedded in Professor Wolfe’s team, which includes clinical and healthcare professionals as well as experts in IT and Data Science. Professor Jeremy Yates and Dr. Maria Marcha from DiRAC will also provide supervision on various aspects of data science and machine learning.
The project will be managed through weekly meetings with supervisors and larger monthly group meetings. A day-to-day supervisor will also be assigned. This support is essential in a busy NHS research environment.
The project will involve organising healthcare data to develop or train Analytical/AI/ML-based models for individuals, families, and communities. You will build a tool that conveys important information to clinicians and healthcare providers. To do this, you will work closely with clinicians who write the notes, order tests, and prescribe treatments to construct the necessary databases. This work will help you understand what constitutes an alert, what feedback is required, and how it should be delivered. This is vital for developing a tool that clinicians will trust.
The project will be managed through weekly meetings with supervisors and larger monthly group meetings. A day-to-day supervisor will also be assigned. This support is essential in a busy NHS research environment.
The contribution will be a proof-of-concept tool that ingests selected data from primary (GP) and secondary (hospital) healthcare databases, as well as patient-entered data (e.g., symptom control). This tool will automatically update at the individual level as new data is entered. It will adjust for any changes to population health that the data reveals. If a change raises concern, an alert will be sent to the relevant clinician or healthcare manager.
The project will be managed through weekly meetings with supervisors and larger monthly group meetings. A day-to-day supervisor will also be assigned. This support is essential in a busy NHS research environment.
We are looking for individuals with:
The candidate is expected to be an active member of the team, engaging in the use of advanced methods to assess how patterns in the use of medicines evolve over time for patients, focusing on common and rare medicines.
With support from the team, the candidate will be expected to produce work of sufficient quality that it will be suitable for publication in peer-reviewed journals. This will also form the basis of the report submitted at the end of the placement.
An alert tool to improve individual and population health. This project will involve using the aforementioned data to develop a proof-of-concept tool that can be considered for the Learning Health System. These data consist of detailed numerical data and non-numerical data such as clinicians’ notes, health data codes, and other forms of data such as socio-economic and mental health data.
The output will be a tool that can send alerts to the relevant clinicians. Clinicians will then assess the efficacy of the tool and its alerts, and you will work with them to improve the efficacy of the tool.
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.
Applications are now closed. New Innovation Placements will be advertised on our social media and via the DiRAC all user email.
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
