Nnennaya Kanu
5 months ago
Triple-negative and hereditary breast cancer UCL (University College London) in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Funding is available for students with Home tuition fee status only. The fellowship covers tuition and stipend for eligible candidates. International students are not eligible for this funding.
Deadline
Aug 1, 2026
Country
United Kingdom
University
University College London

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About this position
A fully funded PhD position is available at University College London (UCL) to study triple-negative and hereditary breast cancer, beginning September 2026. The project is supervised by Professor Nnennaya Kanu (UCL) with secondary supervision from Professor Elinor Sawyer (King’s College London), and support from a multidisciplinary team. The research will use long-read genome sequencing and computational approaches to investigate how structural variants and epigenetic changes contribute to inherited cancer risk, and to study tumour heterogeneity and evolution in triple-negative breast cancer.
The student will analyze data from families with a predisposition to breast cancer and from tumour samples, applying and developing bioinformatics tools to identify novel variants and reconstruct tumour phylogenies. Training will be provided in genomics, sequencing technologies, and computational biology. Applicants should have strong programming skills (Python, R, or Bash), familiarity with high-throughput sequencing data, and a background in computational biology, bioinformatics, or genomics.
Prior experience in cancer genomics is a plus but not required. Funding is restricted to candidates with Home tuition fee status. Full details and application instructions are available at the provided link. The application deadline is August 1, 2026.
Funding details
Funding is available for students with Home tuition fee status only. The fellowship covers tuition and stipend for eligible candidates. International students are not eligible for this funding.
What's required
Applicants should have a background in computational biology, bioinformatics, genomics, or a related discipline. Strong programming skills in Python, R, or Bash and familiarity with high-throughput sequencing data are essential. Prior experience with cancer genomics is advantageous but not required. Candidates should have a keen interest in cancer biology, data integration, and method development. Only students with Home tuition fee status are eligible for funding.
How to apply
Review full project details and application instructions at https://lnkd.in/e5Gci58J. Prepare your application materials as specified. Apply online via the provided link before the deadline. Contact the supervisors for further information if needed.
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