MSc Data & Computational Science
Graduate Taught (level 9 nfq, credits 90)
The MSc in Data and Computational Science is designed for students from highly quantitative disciplines who wish to work in data analytics or computational science.
• 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 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 handson experience in computational science and will allow you to apply the key theoretical and practical skills by working on a challenging research topic.
Who should apply?
Full Time option suitable for:
Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. Yes
Computational science is at the crossroads between modern applied mathematics and statistics, and our programme recognizes this fact by combining aspects of both in a unique set of tailored modules including scientific computing, mathematical modelling, and data analytics.
Vision and Values Statement
This programme is aimed at students who wish to gain a deep understanding of applied mathematics, statistics and computational science at the graduate level. The programme 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 industry or in academia.The taught modules in the programme provide a thorough grounding in the areas of applied mathematics, statistics and computational science; the (supervised) research project introduces the students to an area of computational research. 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. We expect our students to become autonomous learners and researchers capable of setting their own research agenda. 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. We value students who already have a strong numerate training and are motivated to take further their knowledge in this area. We aim to provide a teaching and learning environment that develops confidence and independence through a wide variety of interactive formats, both inside and outside the classroom.