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MSc Computational Cancer

  • DeadlineStudy Details: 1 year full-time

Masters Degree Description

Be part of the revolution in cancer research and computational science with this interdisciplinary Master’s at UCL. Delivered jointly by UCL Medical Physics and Biomedical Engineering and the UCL Cancer Institute, this programme equips you with cutting-edge skills at the forefront of healthcare innovation.

A revolution is underway in cancer research, transforming a field once driven by the collection of experimental evidence into one powered by data analysis, modelling, and computational insight.

This Master’s programme will equip you with the skills to apply cutting-edge computational techniques, including artificial intelligence, dynamical modelling, and data science, to some of the most pressing questions in cancer research. You will gain advanced expertise in computational methods and cancer biology, and contribute to pioneering research aimed at deepening our understanding of this complex disease.

Entry Requirements

A minimum of an upper second-class Bachelor's degree in a relevant subject from a UK university or an overseas qualification of an equivalent standard.

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Fees

For fees and funding options, please visit website to find out more.

Student Destinations

As a postgraduate student at UCL, you will develop a robust set of cross-disciplinary skills and knowledge that can be applied across a wide range of industry and healthcare settings. These include expertise in computational modelling, data science, and artificial intelligence, alongside the domain-specific understanding essential for careers in the life and medical sciences.

Working alongside world-leading scientists, engineers, and healthcare professionals, you will also strengthen key professional skills such as project management, communication, and teamwork, ensuring you are well prepared to contribute effectively in any organisation.

Module Details

Compulsory modules

  •  Basic Biology and Cancer Genetics
  •  Curating Cancer Data
  •  Computational Modelling and Analysis of Cancer Dynamics
  •  Computational Cancer Research Project

Optional modules

  •  Radiotherapy Physics
  •  Machine Learning in Medical Imaging
  •  Applied AI in Medical Imaging
  •  Precision Cancer Medicine
  •  Multi-Omics and Cancer Evolution
  •  Applied Digital Pathology
  •  Fundamentals of Subtyping in Pathology

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