Eczema, or atopic dermatitis, ranks among the most common allergic skin conditions worldwide. It brings unpredictable flares of intense itching, redness, and discomfort that disrupt sleep, work, and daily life for millions. Patients and clinicians currently react after symptoms appear. No reliable tool exists to forecast individual changes in severity days ahead. That gap is about to close.
Imperial College London is offering a fully funded PhD studentship in mechanistic and interpretable AI for personalised eczema severity forecasting. Starting in October 2026 as part of the AI for Healthcare Programme and the Tanaka Group, this project sits at the intersection of artificial intelligence, bioengineering, clinical medicine, and industry collaboration with Pierre Fabre Laboratories. For researchers passionate about applying advanced machine learning to real healthcare problems, this is a rare chance to develop tools that could transform how people manage a chronic disease.
Scholarship Summary
- Host Country: UK
- Host University: Imperial College London
- Scholarship Type: PhD Scholarships
- Eligible Countries: UK
- Scholarship Benefits: Full tuition fee, Living stipend, etc.
The Challenge: Why Eczema Needs Better Forecasting Tools
Eczema severity fluctuates in highly individual ways. Triggers range from skin barrier disruption and microbiome shifts to environmental factors and immune responses. Existing approaches often rely on retrospective assessment or black-box models that deliver predictions without explaining the underlying biology. Clinicians and patients struggle to trust or act on opaque forecasts.
This PhD addresses exactly that limitation. The research will integrate three rich data streams: smartphone images of affected skin, patient-reported severity scores and outcomes, and measurements of skin barrier function plus microbiome composition. These multimodal inputs will feed into a Bayesian modelling framework that embeds known disease mechanisms. The result? Predictions that are not only accurate but explicitly linked to biological drivers. A forecast might indicate elevated risk because of rising pathogenic bacteria on compromised barrier skin, giving both patients and doctors clear, actionable insight.
The long-term vision includes a smartphone application that empowers individuals to anticipate flares, understand personal drivers of their condition, and make informed treatment decisions. This moves eczema care from reactive to proactive and personalised.
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What Makes This Project Distinctive: Mechanistic and Interpretable AI
Many AI systems in healthcare function as black boxes. They achieve high accuracy yet offer little transparency, limiting clinical adoption. This studentship prioritises mechanistic and interpretable AI. By grounding models in biological knowledge within a Bayesian framework, the work produces forecasts that clinicians can interrogate and patients can understand.
The approach builds on prior advances from the Tanaka Group, including tools for automated eczema severity assessment from images and personalised prediction frameworks such as EczemaPred. The new project extends these foundations by fusing imaging, self-reported data, and molecular measurements into a unified, explainable system. Skills developed will span Bayesian modelling, time-series forecasting, computer vision, statistical analysis of biomedical data, and translational collaboration.
Funding supports attendance at leading AI conferences including ICML, AISTATS, and MLHC, giving the student visibility and networking opportunities at the highest level.
World-Class Supervision and Industry Partnership
You will work under an interdisciplinary supervisory team:
- Professor Reiko Tanaka (Department of Bioengineering) as AI supervisor, leading the Biological Control Systems Lab focused on computational systems biology and medicine for allergic diseases.
- Professor Adnan Custovic (National Heart and Lung Institute) as clinical supervisor, bringing deep expertise in allergy and respiratory conditions.
- Dr Gwendal Josse from Pierre Fabre Laboratories as industry supervisor, connecting academic research to pharmaceutical development and real-world application.
This combination ensures the science remains rigorous while staying grounded in clinical need and commercial translation. Pierre Fabre’s involvement opens pathways for impact beyond the academy. The project is based in Bioengineering and forms part of Imperial’s AI for Healthcare Programme, which trains researchers to innovate at the AI-healthcare interface.
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Funding Package: Fully Supported for Home Students
The studentship is fully funded for applicants with Home (UK) fee status only. It covers tuition fees and provides a bursary of £23,805 per year. Eligible students who join the TechExpert pilot can receive an enhanced stipend of £31,000 per annum. Support lasts for 3–4 years. Additional research and conference travel funds are included.
Only new entrants are eligible; current students on the course cannot apply. The opportunity is open to prospective full-time doctoral researchers starting in the 2026/2027 academic year. One award is available.
Who Should Apply for Fully Funded PhD Studentship in Mechanistic and Interpretable AI: Ideal Candidate Profile
Imperial seeks a highly motivated researcher who thrives in collaborative, interdisciplinary settings and is eager to engage with diverse scientific perspectives. The ideal applicant demonstrates:
- 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 environments.
- Genuine interest in applying AI to real-world healthcare challenges.
Entry to the AI for Healthcare Programme is competitive. Applicants typically hold or expect a First-Class undergraduate degree plus Distinction-level Master’s (or equivalent) in a relevant field, with core strengths in mathematics, coding, and statistics. Additional experience in machine learning, computer vision, biology, or medicine is advantageous. Full details on programme requirements appear on the AI for Healthcare application pages.
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How to Apply for Fully Funded PhD Studentship in Mechanistic and Interpretable AI and Key Deadlines
Applications are handled through the AI for Healthcare Programme. Visit the official training and application information at https://ai4health.io/apply/ and https://ai4health.io/training/ for entry requirements, process steps, and current deadlines. Programme rounds for 2026 include early deadlines in February and April, with further opportunities for Home candidates on a rolling basis until places are filled. The specific scholarship page lists an application deadline of 3 August 2026; always check the latest guidance as processes can update.
Explore the Tanaka Group research at https://www.rtanakagroup.com/ to understand the broader scientific context. The official scholarship overview is available at https://www.imperial.ac.uk/study/fees-and-funding/scholarships-search/mechanistic-and-interpretable-ai-for-personalised-eczema-severity-forecasting-phd-studentship-20262027.php.
For enquiries, contact ai4health-admissions@imperial.ac.uk. Prepare a strong CV, transcripts, and a focused personal statement highlighting your interest in AI for healthcare, relevant technical skills, and motivation for this project.
Why This Opportunity Stands Out
Few PhD positions combine cutting-edge interpretable AI methods, multimodal biomedical data, direct clinical collaboration, and industry partnership with a leading pharmaceutical company. The work has clear translational potential: a smartphone tool that helps patients anticipate flares and understand their biology could meaningfully improve quality of life for people living with eczema.
You will join a vibrant research environment at one of the world’s top universities, gain experience spanning academia and industry, and contribute to a field where AI is rapidly reshaping dermatology and personalised medicine. Conference support and the possibility of an enhanced stipend further strengthen the package.
Eczema’s unpredictability has long limited patients’ sense of control. Mechanistic and interpretable AI offers a path toward forecasts that are both accurate and meaningful. If you have the quantitative background, curiosity about biological systems, and drive to create tools that matter clinically, this fully funded PhD studentship in AI for personalised eczema severity forecasting at Imperial College London deserves serious consideration.
Review the programme pages, contact the admissions team with questions, and prepare your application. The October 2026 start date is approaching, and places are limited. This is more than a studentship; it is a chance to help redefine how a common chronic condition is understood and managed.