Data & Computational Science
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.
| Award Name | Degree - Masters (Level 9 NFQ) |
|---|---|
| NFQ Classification | Major |
| Awarding Body | National University of Ireland |
| NFQ Level | Level 9 NFQ |
| Award Name | NFQ Classification | Awarding Body | NFQ Level |
|---|---|---|---|
| Degree - Masters (Level 9 NFQ) | Major | National University of Ireland | Level 9 NFQ |
Duration
1 year full-time.
Entry Requirements
This programme is intended for applicants who have an Upper Second class honours degree or higher, or the international equivalent, in a highly quantitative subject such as Mathematics, Physics, Statistics, Engineering.
Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element), or equivalent.
School of Mathematics and Statistics Application Process FAQ
These are the minimum entry requirements – additional criteria may be requested for some programmes
Careers / Further progression
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 past graduates from this programme and other similar past programmes in the School work in firms including, ICT companies (e.g. Amazon, Meta, Geowox, Sage, Version 1, Vodafone), the financial services industry (e.g. Allianz, Aon, Deloitte, Fidelity Investments, KPMG, Permanent TSB) and other data-intensive businesses (e.g. Accenture, IBM, Intel).
Further information
Next Intake: 2024/2025 September.
MSc Data & Computational Science (T306) Full Time
EU fee per year - € 9300
nonEU fee per year - € 22530
***Fees are subject to change
Tuition fee information is available on the UCD Fees website.
UCD offers a number of graduate scholarships for full-time, self-funding international students, holding an offer of a place on a UCD graduate degree programme. For further information please see International Scholarships.
How to apply?
The following entry routes are available:
MSc Data & Computational Science FT (T306)
Duration 1 Years
Attend Full Time
Deadline Rolling*
* Courses will remain open until such time as all places have been filled, therefore early application is advised
Apply online at www.ucd.ie/apply and find the programme using the unique programme identifier: T306
For queries, please email dataandcomp@ucd.ie
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.
For queries, please email us at dataandcomp@ucd.ie
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
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.
Course Description
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.
Core Modules in Computational Science and Mathematics
Optimisation in Machine Learning
Applied Matrix Theory
Uncertainty Quantification
Data Programming with Python
Data Programming with R
Core Modules in Statistics and Data Analytics
Probability and Statistics
Predictive Analytics
Multivariate Analysis
Statistical Machine Learning
Bayesian Analysis
Optional Modules Include
Machine Learning and AI
Scientific Computing
High-performance Computing
Mathematica for Research
Numerical Algorithms
Time Series Analysis
Monte Carlo Inference
Modules and topics shown are subject to change and are not guaranteed by UCD
Analyze and interpret data, find patterns and draw conclusions
Apply computationally based techniques to formulate and solve problems
Approach problems in an analytical, precise and rigorous way
Demonstrate an in-depth understanding of the interface of applied mathematics, statistics and computational science.
Demonstrate familiarity with the areas of data and computational science currently under active research
Give oral presentations of technical material at a level appropriate for the audience
Model real-world problems in an applied mathematical or statistical framework
Prepare a written report on technical content in clear and precise language
Undertake excellent research at an appropriate level, including survey and synthesize the known literature
Use the language of logic to reason correctly and make deductions
Work independently and be able to pursue a research agenda