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Graduate Studentships

MRC Cancer Unit - PhD Opportunities, 2018

The Medical Research Council Cancer Unit at the University of Cambridge is a leading centre for cancer research in the UK. Our aim is to undertake research that advances our understanding of the earliest steps in the emergence of cancer, and to use this knowledge for early diagnosis, risk stratification and clinical intervention, through the development of innovative enabling technologies. The Unit is based within the Hutchison/MRC Research Centre on the Cambridge Biomedical Campus, and possesses excellent research facilities, strong collaborations with clinicians and colleagues in other disciplines, and a vibrant and supportive working environment.

We will have a number of PhD opportunities for entry in October, 2018.  Fully funded studentships are available to eligible candidates (see Eligibility and Funding section for details) for the following PhD research projects:


  • Computational models of channel dysregulation in oesophageal carcinogenesis

             Dr Ben Hall and Professor Rebecca Fitzgerald

This is an opportunity for someone interested in working in a dynamic collaborative environment across computational biology and molecular biology of cancer evolution. The project would involve developing and applying machine learning models for ion dysregulation in respect to oesophageal cancer based on primary patient data. These predictions can then be tested in in-vitro model systems.

Ion channels play a major role in the development and control of cellular behaviour. They constitute a third of all genes in the human genome, and represent half of known drug targets. They have a further role in the control of the cancer phenotype and the progression of the disease. This has been observed in a variety of systems, but is of particular importance in upper gastro-intestinal cancers where there is a long established role for the effects of acid reflux and more recent data identifying potential ion channel tumour suppressors. This project would initially use machine learning-based approaches to understand how ion channels change in cancer progression, before focusing in on the behaviour individual proteins using either experimental or theoretical approaches. The ideal candidate should be able to demonstrate a good level of computer proficiency, and interest/experience in working with biological problems. Direct experience of working with large datasets would also be an advantage.

More information about the research undertaken in the Hall lab and by Rebecca Fitzgerald can be found here: and


  • Investigating the metabolic heterogeneity in cancer

             Dr Christian Frezza and Dr Alessandro Esposito

Dysregulated metabolism is an established hallmark of cancer. The metabolic determinants of transformation have been extensively investigated, revealing common metabolic features of cancer, including activation of glycolysis and nucleotide biosynthesis. However, whether these features are shared by distinct clones within a solid tumour, or if metabolic heterogeneity exists is still matter of debate. One of the major hurdles to investigate this aspect of cancer metabolism is the lack of appropriate tools to investigate cellular metabolism at a single-cell level. With this PhD project, we want to establish a new experimental platform using state-of-the-art quantitative microscopy techniques and metabolomics to determine the spatio-temporal features of the metabolic reprogramming of cancer. Previous experience in cancer biology, cell metabolism, molecular biology, and microscopy are distinct advantages. This project will be carried out in the context of an exciting multidisciplinary collaboration between the Frezza lab and Dr Alessandro Esposito.

More information about the research undertaken in the Frezza lab and by Alessandro Esposito can be found here: and


  • Defining mechanisms of immune dysfunction in the tumour microenvironment nvestigating the metabolic heterogeneity in cancer

             Dr Jacqui Shields

Although tumours frequently contain immune infiltrates, our immune system is often unable to mount an effective anti-tumour response, and rather than clearing the lesion, immune populations may promote disease progression and metastasis. Despite these observations, the mechanisms employed by a growing tumour to avoid immune destruction remain unclear.  However, recent evidence indicates that non-cancerous support cells within tumours, referred to as the stroma, may play a role.  The Shields group aims to determine how and when the stroma is able to orchestrate immune dysfunction during tumour evolution, both in the local microenvironment and downstream lymph nodes. This project will take an innovative approach that integrates bioengineering principles, novel in vitro systems, state-of-the-art imaging techniques and in vivo tumour models. Our long-term goal is to translate this knowledge into targeted therapeutic platforms capable of restoring the anti-tumour response.

More information about the research undertaken in the Shields lab can be found here:

  • Artificial intelligence and deep learning approaches for deciphering genome regulation in carcinogenic systems

             Dr Shamith Samarajiwa

Cancer is a collection of over 300 different complex diseases where genetic mutations, chromosomal aberrations, epigenomic modifications and interactions with the components of the tumour microenvironment all play a role in carcinogenesis. The Samarajiwa group integratively studies how the perturbations of gene, (epi)genome and chromatin structure regulation contributes to carcinogenic processes. Large multi-dimensional datasets from experimental studies (both functional genomic and cancer genomic data) will form the raw material to develop state-of-the-art hybrid computational biology and artificial intelligence based approaches to understand regulatory rules in pro and anti carcinogenic processes. In particular, deep learning (and machine learning) approaches will be developed or applied to discover high-level regulatory features in multidimensional data-sets and to improve performance over traditional statistical or computational models. A potential outcome would be to gain an understanding of interacting regulatory layers within complex biomedical datasets with the long term aim of identifying regulatory processes that can be targeted for designing anti-cancer therapeutics. This multidisciplinary project will provide the ideal candidate with the required quantitative skills, an exciting opportunity to build expertise in computational genomics, data science and cancer systems biology.

The successful candidate should have a good first degree in a quantitative field (mathematics, computer science, data science, statistics, engineering or physics) and preferably a masters degree in machine learning, deep learning or computational biology (with machine learning expertise). Knowledge of biology not required.

More information about the research undertaken in the Samarajiwa lab can be found here:


Eligibility and Funding:

We welcome applications from those holding, or expecting to obtain at least an upper second class degree (or equivalent) in a relevant scientific subject.  These studentships are funded by the Medical Research Council and are open to UK and EU applicants only.  Other international students are not eligible to apply.  UK applicants will be eligible to receive full funding of University and College fees and a stipend of £18,000 p.a. EU applicants will be funded on a fees-only basis, unless they meet the MRC's eligibility criteria (visit the MRC website for further details:  Successful applicants will be registered with the University of Cambridge.


How to apply:

All applications will need to be made through the University Application Portal.  Please visit: for further information about the programme and to access the Applicant Portal.  

 You are allowed to apply for more than one project as part of the same online application.  Whilst making your application please make it clear which project area(s) and principal investigator(s) you are interested in working with.  Your online application will need to include:

  • A CV, including full details of all University course grades to date.
  • Contact details for two academic or professional referees.
  • A personal statement outlining your interest in a specific project area, what you hope to achieve from a PhD, and your research experience to date.

The above information must be provided under relevant sections on the application portal.


Further notes on completing the ‘Research’ section on the application portal

  • In the ‘Research Title’ textbox, if you are applying for one project only, insert the project title.  If you wish to apply for more than one project, insert ‘Cancer Research’.
  • If you are applying for more than one project, in the ‘Research Summary’ textbox, please insert the project titles you wish to apply for.
  • In the ‘Research Supervisor’ textbox, please insert the initials of the Supervisor(s) you wish to consider your application.
  • Please also describe your research experience in the appropriate textbox.

The closing date for applications is 30th November 2017, with interviews expected to take place in December.

Please contact with any other enquiries concerning studentships or eligibility criteria.