Scholarship overview
Degree level
Postgraduate doctoral
Value
Fully funded for Home (UK) students, covering tuition fees and a bursary of £23,805 per year, rising to £31,000 through the TechExpert pilot, for 3–4 years.
Number of awards
1
Academic year
2026/2027
Tuition fee status
Home
Mode of study
Full time
Available to
Prospective students
Application deadline
03/08/2026
Additional information
Available to applicants in the following departments
- Bioengineering
Eligibility criteria
We are looking for a highly motivated researcher who thrives in a collaborative, interdisciplinary environment and is eager to engage with diverse scientific perspectives.
The ideal candidate will demonstrate:
A strong Master’s degree in Mathematics, Statistics, Machine Learning, Engineering, Computer Science, or a closely related discipline.
Excellent written and oral communication skills.
Strong interpersonal skills and enthusiasm for working across academic and industry settings.
A genuine interest in applying AI to real-world healthcare challenges.
This PhD opportunity is fully funded for applicants with Home (UK) fee status only.
Please note: This scholarship is available to new entrants only. Students already studying the course are not eligible.
Course specific information
Mechanistic and interpretable AI for personalised eczema severity forecasting
This PhD opportunity, starting in October 2026, is based within the AI for Healthcare Programme and the Tanaka Group at Imperial College London, in collaboration with Pierre Fabre Laboratories.
Eczema is the most common allergic skin disease and is characterised by unpredictable fluctuations in symptom severity that significantly affect patients’ quality of life. Currently, no tools exist to forecast changes in eczema severity at the individual patient level.
This project aims to develop mechanistic and interpretable AI tools for personalised eczema severity forecasting by integrating smartphone images of affected skin, patient-reported severity scores and outcomes, and skin barrier and microbiome measurements.
By embedding disease mechanisms within a Bayesian modelling framework, the AI tool will generate predictions explicitly linked to underlying biological drivers, transforming black-box forecasts into clinically actionable, biologically grounded risk assessments. This approach will enable explainable predictions that are meaningful to both patients and clinicians, supporting more personalised and informed disease management.
Supervisory team
You will be supervised by an interdisciplinary team with complementary expertise spanning AI, clinical medicine and industry:
AI supervisor: Professor Reiko Tanaka, Department of Bioengineering.
Clinical supervisor: Professor Adnan Custovic, National Heart and Lung Institute.
Industry supervisor: Dr Gwendal Josse, Pierre Fabre Laboratories.
Application process
Please visit the AI for Healthcare training webpage for further information about the entry requirements and application process for the AI for Healthcare Programme.
Applicants can also visit the Tanaka Group website to learn more about the research area.
For enquiries, please contact ai4health-admissions@imperial.ac.uk.
Additional information
This is a unique opportunity to conduct impactful, translational research at the intersection of AI, bioengineering and clinical medicine, with direct collaboration with a leading international pharmaceutical company.
The research has the potential to transform how patients manage eczema by empowering them to anticipate symptom changes, understand the biological drivers behind their condition and make informed treatment decisions through a smartphone application.
The studentship also includes funding support to attend leading AI conferences such as ICML, AISTATS and MLHC.
Eligible doctoral students who opt to participate in the TechExpert pilot may receive an enhanced stipend of £31,000 per annum. The enhanced stipend is available to doctoral students with Home (UK) fee status only.
Contact
If you have any additional questions, please contact us at ai4health-admissions@imperial.ac.uk.