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University of Cambridge

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University of Cambridge PhD Studentship

PhD studentship in breast cancer biomarkers, systems pathology and deep learning University of Cambridge in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

PhD studentship at the University of Cambridge; the post is a funded studentship, but no stipend, tuition, or fee details are stated in the post.

Deadline

Oct 16, 2026

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Country

United Kingdom

University

University of Cambridge

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Keywords

Computer Science
Deep Learning
Biology
Predictive Modeling
Medical Science
Breast Cancer
Statistics
Spatial Transcriptomic

Suggested scholarships

About this position

PhD studentship at the University of Cambridge in breast cancer, systems pathology, deep learning, spatial transcriptomics, and imaging mass cytometry.

The Ali Lab at the Cancer Research UK Cambridge Institute is recruiting a student for a project titled “Discovery of rational therapeutic biomarkers in breast cancer by systems pathology and deep learning.” The project aims to use modern multiomic spatial methods and deep learning to identify therapeutic biomarkers, quantify tissue heterogeneity, and understand how tissue architecture shapes response to novel breast cancer therapies.

This is a strong fit for candidates interested in quantitative pathology, spatial cancer biology, predictive modelling, and large-scale data processing/analysis. The post mentions that applicants are invited from quantitative disciplines such as computer science, AI, and mathematics, while biologists and clinicians with computational experience are also encouraged.

Training will include cancer pathology, highly multiplexed imaging, and predictive modelling in a collaborative environment spanning clinicians, pathologists, computational biologists, and cancer biologists.

Deadline: 16 October 2026. Start date: 1 October 2027. Apply through the University Applicant Portal via the postgraduate course page.

Funding details

PhD studentship at the University of Cambridge; the post is a funded studentship, but no stipend, tuition, or fee details are stated in the post.

What's required

Applicants should be graduates in quantitative disciplines such as computer science, AI, or mathematics. Applications from biologists and clinicians with experience in computational methods are also encouraged. The project is suited to candidates interested in cancer pathology, highly multiplexed imaging, predictive modelling, spatial biology, and large-scale data analysis.

How to apply

Apply via the University Applicant Portal using the postgraduate course page. Select October 2027 as the intended start date and submit references when requested.

More information can be found here

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