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The friendly atmosphere at DSI has made my research experience pleasant and unique with a rich cultural experience. Originating from over 30 countries, DSI members interact in a constructive way which makes collaboration easy & fun. DSI has proved to be a different place where a deep connection between members is made, particularly, thanks to various meetings & seminars that are regularly held throughout the year. I was expecting to find myself somewhere like the laboratories and research centres where I previously worked: a place where everyone only cares about his/her business without minding much the quality of life and the relationships with other colleagues. PhD Student at the Data Science InstituteĪfter doing my master's in France, I joined DSI in 2018 to pursue a PhD in computer science &engineering.

The willingness to combine formal scientific work with application-oriented research in projects funded by the European Commission, national agencies or by industry.

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.

A strong background in computer science.

You can find information on research interests and contacts on our website. 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. 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. PhD candidates must have a good honours degree (typically First Class Honours or 2:1) in a relevant area. DSI took its current name in December 2017, to better reflect the range of research, development and outreach activities within in the institute.

In 2014, it became an official research institute of the National University of Ireland Galway under the name Insight Research Institute. 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. 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). Please check the following web page for a list of current projects at the Data Science Institute.Īt 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. 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. 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. 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.

Get the Edge with a Postgraduate Degree from NUI Galway Grainne McNamara - MSc Enterprise Systems Gordan Sands - MSc Medical Physics Biomedical Engineering at NUI Galway Mohammed Hasan – Occupational Health & Safety (MSc) Course Overviewĭata 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.