Cancer Genomics and Data Science at Queen Mary University of London - UCAS

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Course summary

Biomedical science is increasingly data driven and a wide range of state-of-the-art techniques in cancer genomics and data science is required to analyse multi-layer large scale cancer datasets and derive meaningful interpretable results. However, there is a serious shortage of well-trained people who have the relevant skillset and hands-on experience in real world biomedical and cancer data.

  • Join a programme designed and delivered by world-class experts in genomics and data science, who actively develop and apply computational tools to answer research questions
  • Gain hands-on experience using real world patient and experimental data
  • Learn up-to-date analytic techniques and bioinformatics/computational tools in biomedical and cancer research
  • Complete a substantial individual research project to expand your analytic skills and research experience
  • Choose the study option that suits you best: full-time, part-time, on campus or online
Biomedical science is increasingly data driven, as new bioanalytical techniques deliver ever more data about DNA, RNA, proteins, metabolites and the interactions between them in the whole tissue and single-cell levels. A wide range of state-of-the-art techniques in the field of cancer genomics and data science for example modelling, data integration, machine learning and AI is required to analyse multi-layer large scale cancer datasets and derive meaningful interpretable results. However there is a serious shortage of well-trained bioinformaticians, computational biologists and data analysts who have the relevant skillset and experience in real world biomedical and cancer data. This programme is designed to fill the gap between research and employment demands and student training, offering up-to-date modules focusing on “big-data” analyses and enabling these through use of high-performance computing, together with cutting edge research projects and practical training using real world cohort data. You’ll be taught by academics who are actively engaged in developing bioinformatics and computational tools, and applying them in cancer and medical research areas such as genomics, proteomics, evolution, modelling and biomarker discovery. We have an extensive network of academic and industrial collaborators around the UK, who contribute to teaching, co-supervise research projects and provide employment opportunities.

Modules

Please see website for up-to-date module information

Assessment method

Assessment will be, but not limited to, short and long answer coursework, multiple choice questions, presentations and research dissertation. Assessment has been designed to develop and assess a broad range of skills that will be essential for students in their future careers. There will also be a 10,000 word dissertation.


Entry requirements

Potential students are expected to have, or be expecting, a minimum 2:1 in a relevant subject of quantitative background, such as genetics, genomics, maths, physics, engineering and computer sciences. Students with a 2:1 in Biology, Medicine, or a relevant natural sciences subject with strong quantitative skills will also be considered. Applicants with a 2:2 and strong supporting evidence may be considered on an individual basis.


Fees and funding

Tuition fees

No fee information has been provided for this course

Additional fee information

Students enrolling on a postgraduate degree programme are charged tuition fees each year by Queen Mary. The rate you will be charged depends on whether you are assessed as a Home/EU or Overseas student. You can find tuition fees for each course on the course finder pages on our website: https://www.qmul.ac.uk/postgraduate/ Further details about postgraduate taught tuition fees can also be found on our website: https://www.qmul.ac.uk/postgraduate/taught/tuitionfees/
Cancer Genomics and Data Science at Queen Mary University of London - UCAS