Development of a Dermatopathology Foundation Model (PhD)
Develop AI-driven dermatopathology models for melanoma diagnosis and risk stratification within an EU-funded MSCA Doctoral Network.
Best for:Best for computer science graduates with expertise in computational pathology, machine learning, and multimodal data integration, seeking interdisciplinary research in precision medicine.
Overview
This PhD position is part of the Horizon Europe MSCA Doctoral Network SPACE-MEL, which aims to advance spatial single-cell omics technologies for precision medicine. The successful candidate will develop a dermatopathology-specific foundation model for melanoma diagnosis and risk stratification at The University of Manchester. The project involves building a large, harmonised dataset of digitised H&E and IHC images linked to pathology reports, molecular information, and spatial omics data. The candidate will work on computational pathology, visual foundation models, and multimodal learning for digital pathology applications. The role includes research visits to Erasmus MC and Intelligent Biodata, focusing on data curation, model integration, and clinical application. This position offers a prestigious MSCA Fellowship, interdisciplinary training, and exposure to cutting-edge research in spatial biology.
What you'll do
- Develop a dermatopathology-specific foundation model for melanoma diagnosis and risk stratification using digitised H&E and IHC images.
- Build and harmonise a large dataset linking pathology reports, molecular information, and spatial omics data.
- Train and refine a pathology foundation model adapted to dermatopathology applications.
- Integrate histology-derived representations with textual and omics information for diagnostic triage and molecular status prediction.
- Collaborate with Erasmus MC on curation and harmonisation of digitised melanoma images and clinical-pathology data.
- Work with Intelligent Biodata to integrate model outputs with LLM-based approaches and pathology reports.
- Conduct research visits to partner institutions to enhance interdisciplinary collaboration.
- Present research findings at international conferences and workshops.
Requirements
Degree required: Master’s degree or equivalent in Computer Science or a related discipline (minimum Upper Second class UK honours degree or equivalent).
Degree offered: PhD
Language: English; excellent proficiency (written and spoken)
Instruction: English
- Proven expertise in computational pathology or machine learning.
- Experience with multimodal data integration and digital imaging.
- Strong programming skills (e.g., Python, R).
- Familiarity with medical imaging data formats (e.g., DICOM, TIFF).
- Knowledge of spatial omics data analysis techniques.
- Applicant must not already hold a doctoral degree.
- Mobility rule: researchers must not have resided or carried out their main activity in the United Kingdom for more than 12 months in the 36 months immediately before recruitment.
Funding & terms
How to apply
Deadline: 2026-10-30 (Europe/London)
Interested candidates must first contact the Primary Supervisor, Martin Fergie, to discuss their interest and suitability for the project. Formal applications should be submitted through the Faculty of Biology, Medicine and Health Doctoral Academy website, selecting PhD Biomedical Imaging Sciences as the programme.
- CV
- Cover letter
- Academic transcripts (Bachelor’s and Master’s degrees)
- Two reference letters
Contact
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