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Cruk ci phd studentship: development and application of computational tools for the early detec[...]

Cambridge
Minderoo Centre for Technology and Democracy
Posted: 15 September
Offer description

Overview

CRUK CI PhD Studentship: Development and application of computational tools for the early detection and deconstruction of chromosomal instability in cancer

PhD Studentship: Development and application of computational tools for the early detection and deconstruction of chromosomal instability in cancer at the Minderoo Centre for Technology and Democracy, Cancer Research UK Cambridge Institute.


Details

Supervisor(s): Professor Florian Markowetz

Department/location: Cancer Research UK Cambridge Institute

Deadline for application: 17 October 2025

Course start date: 1 October 2026


Project summary

Professor Florian Markowetz wishes to recruit a student to work on the project entitled: "Development and application of computational tools for the early detection and deconstruction of chromosomal instability in cancer". The project aims to build upon previous work developing computational methodologies to detect and deconvolute mutational processes associated with chromosomal instability (CIN), leverage single-cell DNA sequencing to understand CIN heterogeneity, and develop and implement machine learning and AI models for imaging data. The student will develop new models for early detection of CIN cancers, apply advanced computational methods and ML/AI approaches to improve detection and understanding of CIN cancers, and aim to build models to improve patient survival and treatment outcomes.

There is flexibility for the applicant to focus on cancer genomics methods or early detection in imaging, with the possibility of cross-disciplinary research combining both areas, depending on candidate preferences.


References / Further reading

[1] A pan-cancer compendium of chromosomal instability http://doi.org/10.1038/s41586-022-04789-9

[2] scAbsolute: measuring single-cell ploidy and replication status http://doi.org/10.1101/2022.11.14.516440

[3] Triage-driven diagnosis for early detection of esophageal cancer using deep learning http://doi.org/10.1101/2020.07.16.20154732


Preferred Skills / Knowledge

We are seeking a highly motivated and independent candidate with strong analytical skills. The candidate should have a strong desire to develop novel computational methods and ML/AI tools to address challenging problems related to early detection and chromosomal instability in cancer. A background in computational biology, mathematics, or computer science is preferable, though we welcome applicants with relevant biological degrees with sufficient computational background.


Funding

This four-year studentship is funded by Cancer Research UK Cambridge Institute and includes full funding for University fees and an index-linked stipend starting at £22,500 for four years.


Eligibility

We welcome applications from both UK and overseas students. Applications are invited from recent graduates or final-year undergraduates who hold or expect to gain a First/Upper Second Class degree (or equivalent) in a relevant subject from any recognised university worldwide. Applicants with relevant research experience, gained through Masters study or working in a laboratory, are strongly encouraged to apply.


How to Apply

Please apply via the University Applicant Portal. For further information about the course and to access the Applicant Portal, visit: https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc. You should select to commence study in October 2026.


Additional Information

To complete your online application, you will need to answer/provide the following: Choice of project and supervisor (name the project with reference code and supervisor). You are permitted to apply for up to three projects. Course-specific questions: details of your Research Experience (up to 2,500 characters) and your Statement of Interest (up to 2,500 characters) explaining why you wish to be considered and what qualities you will bring.

Supporting documents: Academic transcripts, Evidence of English competence (if appropriate), Details of two academic referees, CV/resume.

Deadline: The closing date for applications is 17 October 2025 with interviews expected to take place in the week beginning 5 January 2026. The University Equality, Diversity and Inclusion statement applies; the University has a responsibility to ensure all employees are eligible to live and work in the UK. Please quote reference SW47203 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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