Course Overview

Data Science is concerned with the development of scalable methods for the curation and analysis of large data sets, in order to derive insights and actionable knowledge from these for predictive analytics and other aspects of decision support. Methods in Data Science typically build on best practices in machine learning and statistics with applications in the analysis of structured data as well as of semi-structured and unstructured data, including numerical, textual and image data. Data sources can be in Internet of Things and other sensor data streams, social media, large text collections such as reporting, image collections, video material, etc. In addition to machine learning and statistics, scientific methods specific to each data type will originate from areas including Natural Language Processing, image processing, stream reasoning, etc.

Please check the following web page for a list of current projects at the Data Science Institute. 

Programmes Available

Structured PhD (Data Science), full-time & part-time 
Masters in Applied Science MAppSc (Data Science), full-time and part-time
Masters in Engineering Science MEngSc (Data Science), full-time and part-time

Duration:
4 years (full-time structured PhD), 2 years (full-time Masters)
6 years (part-time structured PhD), 3 years (part-time Masters)

Applications are made online via the NUI Galway Postgraduate Applications System

Associated Research Institute

Data Science Institute (DSI)

About us:
At the Data Science Institute (DSI), we research technologies at the convergence of Computer Science, Web Science and Artificial Intelligence to build a fundamental understanding of how information and knowledge are increasingly driving society through digital processes, and of the tools, techniques and principles supporting a data-enhanced world.

History:
The Data Science Institute at NUI Galway (DSI) originally started as a Centre for Science, Engineering and Technology (CSET) in 2003 with funding from Science Foundation Ireland under the name Digital Enterprise Research Institute (DERI). It has hosted part of the Insight Centre for Data Analytics since it was established in 2013 by Science Foundation Ireland, and also receives funding from EU Framework Programmes, Enterprise Ireland, IRC, and industry. In 2014, it became an official research institute of the National University of Ireland Galway under the name Insight Research Institute. DSI took its current name in December 2017, to better reflect the range of research, development and outreach activities within in the institute.

Learning Outcomes

Entry Requirements

PhD candidates must have a good honours degree (typically First Class Honours or 2:1) in a relevant area. Interested candidates should begin by contacting a member of DSI research and academic staff whose research interests are most closely aligned to their own research interests.

Masters candidates must hold at least a 2nd Class Honours Primary Degree in a related subject area or hold a Primary Degree in a related area without honours (which is acceptable to College) and have practical experience in the subject area over a period of not less than three years.

You can find information on research interests and contacts on our website.

We expect:

  • A strong background in computer science
  • Research interests in Data Science, Natural Language Processing, Information Management, Systems Development, Logic, Ontology Languages, Semantic Web, Semantics in Business Information Systems, Linked Data, Machine Learning, IOT, sensors, stream reasoning.
  • The willingness to combine formal scientific work with application-oriented research in projects funded by the European Commission, national agencies or by industry.

Who’s Suited to This Course

Current research projects

The Data Science Institute actively seeks funding from a wide variety of sources including national & international funding agencies and from private industry. The following list shows some of the more prominent sources that fund research activity at DSI:

  • SFI Insight Centre for Data Analytics
  • SFI Confirm Centre for Smart Manufacturing
  • SFI Lero—The Irish Software Research Centre
  • SFI Vistamilk—Milk by Design
  • EU Horizon 2020
  • Enterprise Ireland
  • Irish Research Council
  • Other Irish State funding including Department of Health and Department of Public Expenditure & Reform
  • Private Industry Funding

Please check the following web page for a list of current projects at the Data Science Institute. 

 

 

Current funded research opportunity

Work Placement

Related Student Organisations

Career Opportunities

Find a Supervisor / PhD Project

If you are still looking for a potential supervisor or PhD project or would like to identify the key research interests of our academic staff and researchers, you can use our online portal to help in that search

Research Areas

Data science, Linked Data, Semantic Web, Internet of Things (IOT), Natural Language Processing (NLP), information mining, knowledge discovery, reasoning and querying, machine learning, blockchain, social software, big data, bioinformatics, knowledge management, graph mining, knowledge graphs, smart enterprise, ontologies, ontology engineering.

 

Researcher Profiles

Academic Staff

Research Staff

Course Fees

Fees: EU

€5,750 p.a. 2018/19

Fees: Non EU

€14,750 p.a. 2018/19

Extra Information

EU Part time:  Year 1 [2018/19] €3,910. p.a.

Contact Us

Please contact directly the relevant research leader, listed below.

What Our Students Say

Ríona

Ríona Ní Ghriallais |   Biomedical Engineering PhD

For my research, I investigate medical devices for the femoral artery, the major artery of the leg. I became interested in research after completing my final year project in the fourth year of my undergraduate Biomedical Engineering degree. Studying Biomedical Engineering at NUI Galway ntroduced me to the fascinating world of medical devices. The degree provided me with the fundamental skills set required to begin a career as an engineer along with the opportunity to study a broad range of subjects. From this I found those that interested me the most, which led me towards choosing the topic of my research work.