Teaching

Undergraduate 

C2D3 Computational Biology members have helped set up, run and teach relevant undergraduate courses including Molecular Bioengineering I (Engineering 3G1) and the Part III in Systems Biology. Molecular Bioengineering II (Engineering 4G8) will run for the first time in Lent 2024. They have also co-organised the Cambridge team for the International Genetically Engineered Machines (iGEM) competition from 2005-2012 and 2014, winning many prizes including the Grand Prize in 2009. 

MPhil degree in Computational Biology

The MPhil in Computational Biology is an 11-month course aimed at introducing students to quantitative aspects of biological and medical sciences, including bioinformatics. It is intended for mathematicians, computer scientists and others with similar backgrounds wishing to learn about the subject in preparation for a PhD course or a career in industry. It is also suitable for students with a first degree in biosciences as long as they have strong quantitative skills (which should be documented in their application). 

Wellcome Trust PhD Programme in Mathematical Genomics and Medicine (MGM) 

This programme is no longer recruiting.  

Enquiries: mgmadmin@gen.cam.ac.uk 

Programme Director: Professor Richard Durbin (Genetics; Wellcome Sanger Institute)

Deputy Directors: 

Modern genomics promises not only to help uncover the molecular basis of disease, but also to have a major impact on health care through translation of advances in techniques, computation and knowledge into clinical trials and clinical practice. Quantitative analysis is at the heart of this goal, and there is a pressing requirement for researchers with thorough mathematical and statistical expertise, in addition to training in medical genetics and informatics. 

This PhD programme has been established as a collaboration between the University and the Wellcome Trust Sanger Institute. The programme will provide the opportunity to work at the interface between the mathematical and computational sciences, and genome-scale and translational medical research. We expect that successful applicants will have strong mathematical, statistical and computational skills, and may include exceptional biologists. They will develop quantitative techniques and theoretical approaches and apply them to practical problems in both translational and basic biomedical research. The programme follows a "1 + 3" model, comprising a tailored first year of taught modules and research rotations, followed by a three-year research project. All students will have two supervisors, one from a mathematics, engineering or other quantitative science background, and the second from a genetics or genomics/biomedical background. 

Successful applicants will have the opportunity to undertake research that draws on the unique strengths of the Cambridge region: the successful synergies of NHS and University in translational medical research; genetics, computational and genomics research at the University and the Wellcome Trust Sanger Institute; and the University’s outstanding research and training base in the mathematical sciences. 

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PDF icon MGM PhD information sheet - Jan 2022262.42 KB

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Acts as a gateway for external organisations 

Join us.