Cancer Genomics and Data Science Online MSc
Queen Mary University of London Online
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Qualification

MSc - Master of Science

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Location

Queen Mary University of London Online

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Online

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Duration

1 year

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Qualification

MSc - Master of Science

Location

Queen Mary University of London Online

Study mode

Online

Start date

SEP

Duration

2 years

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Qualification

MSc - Master of Science

Location

Queen Mary University of London Online

Study mode

Online

Start date

SEP

Duration

1 year

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Course info

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 ...Read more

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
  • Study online so you can fit your studies around your other commitments. You can also choose to study in person with our on campus programme.

What you'll study

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.

Career paths

You’ll leave this programme with competence in state-of-the-art analytic workflows and hands-on experience of a wide range of real-life cancer and medical data, so that you will be ready to meet research and industry needs after graduation.

There is high demand for well-trained bioinformaticians and computational biologists to manage, analyse, integrate and visualise “big data”, both in academia and industry. Bioinformatics and data science skills are highly transferable, allowing skilled individuals to move to other sectors, such as data analytics, software development and quantitative finance.

We anticipate that graduates from this programme are likely to move into roles such as:

  • Bioinformatician
  • Data analyst
  • Computational biologist
  • Researcher

In both academia and industry, including large pharmaceutical companies, small and medium-sized enterprises, and start-ups.

Entry requirements

A 2:1 or above at undergraduate level in any subject, provided the degree contains satisfactory study of Mathematics and Statistics. Subjects likely to contain sufficient quantitative elements include Genetics, Genomics, Bioinformatics, Mathematics, Statistics, Engineering, and Computer Science. Applications from those with less quantitatively oriented Natural Sciences degrees, such as Biology and Medicine, are welcome if they have focused on the more quantitative elements of those degrees. Applicants with a 2:2 degrees with relevant content and at least one year of relevant experience, for instance work in industry, analytics, diagnostic labs, scientific research etc, may be considered on an individual basis.

Tuition fees

Students living in

Domestic

£12,250 per year

This information is updated by IDP Connect, or in some cases the institution directly.
Please note: The fees might vary so please make sure you contact the institution for up to date information.

Students from Domestic

This is the fee you pay if the University is in the same country that you live in (England, Scotland, Wales, Northern Ireland)

This is the fee you pay if the University is in the same country that you live in (England, Scotland, Wales, Northern Ireland)

£26,750 per year

This information is updated by IDP Connect, or in some cases the institution directly.
Please note: The fees might vary so please make sure you contact the institution for up to date information.

Students from EU

The amount you'll pay if you come to study here from somewhere in the EU.

The amount you'll pay if you come to study here from somewhere in the EU.

£26,750 per year

This information is updated by IDP Connect, or in some cases the institution directly.
Please note: The fees might vary so please make sure you contact the institution for up to date information.

Students from International

The amount you'll pay if you come to study here from a country outside the EU.

The amount you'll pay if you come to study here from a country outside the EU.

IDP Connect

Uni info

Queen Mary University of London Online
Mile End Road London E1 4NS United Kingdom
Nearest tube station: Mile End  0.2 miles away Nearest train station: Limehouse  0.4 miles away
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