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The MSc Data & Computational Science course is aimed at students who wish to gain a deep understanding of applied mathematics, statistics and computational science at the graduate level. The course will equip such students with the skills necessary to carry out research in these computationally based sciences and will prepare them well for a career either in the industry or in academia. The taught modules in the course provide a thorough grounding in the areas of applied mathematics, statistics and computational science; all students complete project work in data and computational science with the option of (supervised) research dissertation.
We expect our students to gain a thorough understanding of data and computational science at the graduate level, as well as a broad understanding of currently relevant areas of active research and to become autonomous learners and researchers capable of setting their own research agenda.

The programme will equip you to solve complex scientific problems and analyse large data sets using a range of theoretical tools, from deterministic mathematical modelling to Bayesian analysis.
The intensive programming modules will allow you to develop a range of sought-after skills in practical programming and data analytics, including applications in high-performance computing.
Topical application areas are offered each year, including cryptography, numerical weather prediction, and financial mathematics. The dissertation will give you further hands-on experience in computational science and will allow you to apply key theoretical and practical skills by working on a challenging research topic.

What Will I Learn?

1 - Demonstrate an in-depth understanding of the interface of applied mathematics, statistics and computational science.
2 - Demonstrate familiarity with the areas of data and computational science currently under active research
3 - Undertake excellent research at an appropriate level, including survey and synthesise the known literature
4 - Use the language of logic to reason correctly and make deductions
5 - Approach problems in an analytical, precise and rigorous way
6 - Apply computationally based techniques to formulate and solve problems
7 - Model real-world problems in an applied mathematical or statistical framework
8 - Analyse and interpret data, find patterns and draw conclusions
9 - Work independently and be able to pursue a research agenda
10 - Give oral presentations of technical material at a level appropriate for the audience
11 - Prepare a written report on technical content in clear and precise language

Career & Graduate Study Opportunities

Our graduates will be suitably qualified for research at the PhD level at the interface of applied mathematics, statistics and computational science. They will be valued for their technical knowledge and research skills. Equally, our graduates will be in demand by employers for their acquired skills in data analytics and computational and statistical modelling. Recent graduates from this programme work in ICT (including Amazon, IBM, Intel, Meta, Paypal and Vodafone), financial services (including AIB, Aon, Fidelity Investments), and other data-intensive industries (e.g. Accenture, Bosch, EY)