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University of East Anglia UEA: Data Science for Biology
Institution | University of East Anglia UEA View institution profile |
---|---|
Department | School of Computing Sciences |
Web | https://www.uea.ac.uk |
admissions@uea.ac.uk | |
Telephone | 01603 591515 |
Study type | Taught |
MSc
Summary
**Overview**
Immerse yourself in bioinformatics and data analysis, guided by world-class researchers at the forefront of their fields.
Biosciences are increasingly dominated by vast amounts of data, which can scale from molecular levels (genomic, transcriptomic, proteomic, or metabolomic data) to ecological and environmental data collected from large populations or communities. The ability to manipulate, analyse, and interpret these data is pivotal to addressing the biological challenges of the 21st century.
Our interdisciplinary MSc Data Science for Biology is designed to equip you with comprehensive knowledge and skills in data mining, bioinformatics, and statistics. You’ll become proficient in the analysis of biological data, learning essential skills such as statistical analysis, data visualisation, and bioinformatics techniques. You'll master the tools required to analyse complex biological data, including Python and R. You’ll also have exciting opportunities to collaborate with industry partners at the Norwich Research Park, such as the Earlham Institute, John Innes Centre, and Quadram Institute.
Here at UEA, you’ll be part of our vibrant research community within the School of Biological Sciences. We take a uniquely integrated approach, connecting biology at all scales - from molecules, genes, and genomes to populations and ecological communities. In the 2021 Research Excellence Framework, 92% of our research was classified as ‘world-leading’ or ‘internationally excellent,’ offering you unparalleled research opportunities.
With UEA's MSc in Data Science for Biology, you're not just getting a degree; you're opening doors to a world of opportunities. You’ll graduate with in-demand skills that will pave the way for rewarding careers in biotech, medicine, and the life sciences. Along with a wealth of knowledge, you’ll gain prestigious connections and significant research experience. This unique combination will give you a substantial competitive edge, placing you ahead of other graduates in your career or further studies.
**Disclaimer**
Course details are subject to change. You should always confirm the details on the provider's website: **www.uea.ac.uk**
Level | RQF Level 7 |
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Entry requirements | Bachelor Honours degree - 2.2 or equivalent in a Biology related subject. |
Location | University of East Anglia Norwich Research Park Norwich NR4 7TJ |
Fees
Channel Islands | 11775 GBP for Whole course |
---|---|
England | 11775 GBP for Whole course |
Northern Ireland | 11775 GBP for Whole course |
Scotland | 11775 GBP for Whole course |
Wales | 11775 GBP for Whole course |
International | 24500 GBP for Whole course |
Summary
**Overview**
Immerse yourself in bioinformatics and data analysis, guided by world-class researchers at the forefront of their fields.
Biosciences are increasingly dominated by vast amounts of data, which can scale from molecular levels (genomic, transcriptomic, proteomic, or metabolomic data) to ecological and environmental data collected from large populations or communities. The ability to manipulate, analyse, and interpret these data is pivotal to addressing the biological challenges of the 21st century.
Our interdisciplinary MSc Data Science for Biology is designed to equip you with comprehensive knowledge and skills in data mining, bioinformatics, and statistics. You’ll become proficient in the analysis of biological data, learning essential skills such as statistical analysis, data visualisation, and bioinformatics techniques. You'll master the tools required to analyse complex biological data, including Python and R. You’ll also have exciting opportunities to collaborate with industry partners at the Norwich Research Park, such as the Earlham Institute, John Innes Centre, and Quadram Institute.
Here at UEA, you’ll be part of our vibrant research community within the School of Biological Sciences. We take a uniquely integrated approach, connecting biology at all scales - from molecules, genes, and genomes to populations and ecological communities. In the 2021 Research Excellence Framework, 92% of our research was classified as ‘world-leading’ or ‘internationally excellent,’ offering you unparalleled research opportunities.
With UEA's MSc in Data Science for Biology, you're not just getting a degree; you're opening doors to a world of opportunities. You’ll graduate with in-demand skills that will pave the way for rewarding careers in biotech, medicine, and the life sciences. Along with a wealth of knowledge, you’ll gain prestigious connections and significant research experience. This unique combination will give you a substantial competitive edge, placing you ahead of other graduates in your career or further studies.
**Disclaimer**
Course details are subject to change. You should always confirm the details on the provider's website: **www.uea.ac.uk**
Level | RQF Level 7 |
---|---|
Entry requirements | DEGREE CLASSIFICATION: Honours degree - 2.1 |
Location | University of East Anglia Norwich Research Park Norwich NR4 7TJ |
Fees
Channel Islands | 11000 GBP for Whole course |
---|---|
England | 11000 GBP for Whole course |
Northern Ireland | 11000 GBP for Whole course |
Scotland | 11000 GBP for Whole course |
Wales | 11000 GBP for Whole course |
International | 22900 GBP for Whole course |
Join UEA and you’ll belong to a world class university. UEA is a UK Top 25 university (Complete University Guide 2024) and is ranked in the UK Top 30 in the Times/Sunday Times and Guardian University 2024 guides. You’ll also be part of a thriving community located in one of the best places to live in the UK, Norwich. So whether you’re looking to broaden your career choices or develop your passion, discover how you can go further at UEA..
As well as being home to a vibrant campus community, the teaching and research at UEA is deservedly …![endif]-->!--[if>
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