MSc Data & Computational Science

HEA Stimulus Package - Commencing January 2021

Graduate Taught (level 9 nfq, credits 90)

UCD School of Mathematics and Statistics is pleased to announce that the Higher Education Authority (HEA) has agreed to fund ten additional places on the MSc in Data and Computational Science. The programme will commence in January 2021 until December 2021.

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.

Applications are open now for the January 2021 intake. In order to be considered eligible for one of the HEA funded places, completed applications must be submitted online by 5pm Thursday 26th November 2020.

  • 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.


Careers & Employability

The unique combination of modules and skills offered by this programme will equip graduates to work in a range of specific sectors in data analytics, data science, quantitative modelling in finance, and computational science and engineering. This is a new highly specialized programme in the school; recent past graduates from similar programmes in the school work in firms including:

ICT companies (e.g. Google, Paddy Power, LinkedIn)

The financial services industry (e.g. Citi, Deloitte, Geneva Trading, Murex)


Please send any queries to


Curricular information is subject to change


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Eligible participants are listed below as specified by the HEA at


Returners are those who are not in receipt of a payment from the Department of Employment Affairs and Social Protection but who have been out of the work environment for a number of years due to childcare or other caring obligations. They have a previous history of employment but may require upskilling, reskilling or cross-skilling to transition back to the workforce.

To be eligible the applicant must have been:

  • A Homemaker or on other caring duties for a minimum period of 9 of the previous 12 months prior to their application
  • Ordinarily resident in an EU/EEA/UK/Swiss state for at least three of the five years preceding their entry to the programme
  • In addition, the applicant will need to provide supporting documentation to confirm their status as a Homemaker.
  • Applicants must swear a declaration before a Commissioner for attesting to their status.
  • It should be noted that acceptance on to a postgraduate course does not confer any entitlement to DEASP payments or childcare supports.

Returners will not pay any course fees.

The Employed

Applicants who are employed will need to meet the residency requirements, i.e. that the applicant has been ordinarily resident in an EU/EEA/UK/Swiss state for at least three of the five years preceding their entry to the programme.

This category of applicant will also be required to provide a copy of their most recent ‘Employment Detail Summary’ or other relevant revenue documentation.

Applicants who are employed will be required to pay 10% of the course fee.

Formerly Self-employed

To be eligible those who are formerly self-employed must provide a letter/statement from Revenue confirming that the applicant is no longer trading or a similar letter from the applicants (former) accountant should be sufficient.

Alternatively, a participant can swear a declaration stating that they are no longer self-employed. 

Applicants who are self-employed will be required to pay 10% of the course fee.

Recent graduates 

Full and Part time Postgraduate courses are open to recent graduates. However, to participate in these courses, 2020 graduates will be required to pay 10% of the course fee.

Eligible participants must have at least a level 8 qualification or equivalent prior to acceptance onto a course. Exact academic eligibility requirements will be determined by individual providers and may depend on the nature of the course. Providers will be required to have a Recognised Prior Learning (RPL) policy in place. 


Eligible Applicants must be ordinarily resident in Ireland and must meet the nationality and EU residency rules as aligned to Springboard as detailed here

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.

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.

  • Analyse 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

Core modules in simulation and modelling:

  • Mathematica for Research
  • Applied Matrix Theory
  • Communicating for Impact
  • Advanced Computational Science
  • Projects in Maths Modelling
  • Uncertainty Quantification

Core modules in statistics and data analytics

  • Statistical Machine Learning
  • Multivariate Analysis
  • Bayesian Analysis
  • Machine Learning & AI
  • Data Programming with R
  • Data Prog with Python

Optional topical modules, for example:

  • Numerical Algorithms
  • Scientific Programming (ICHEC)
  • Monte Carlo Inference
  • Time Series Analysis - Act App
  • Stochastic Models
  • Data Prog with SAS
  • Stat Network Analysis


Modules and topics shown are subject to change and are not guaranteed by UCD

Places are fully funded; however, some applicants are liable to pay 10% of the course fee. Further information on eligibility can be found here

This programme is intended for applicants who have an Upper Second class honours degree or higher, or the international equivalent, in the primary degree in one of the following:

  • Mathematics, Statistics, Applied Mathematics
  • Financial Mathematics
  • Actuarial Science
  • Business Analytics or Economics with a substantial mathematical and
    statistical component.

Some other applications may be considered, on foot of a discussion with the Programme Director.

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.

Eligible applicants must also comply with requirements as set out by the HEA. Further information on eligibility can be found here Eligible Applicants must also be ordinarily resident in Ireland and must meet the nationality and EU residency rules as aligned to Springboard as detailed here

Apply online at:

and find the programme using the unique programme identifier: T353