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PhD Opportunities at the University of Limerick

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CNGL PhD Studentship available at the University of Limerick, Department of Computer Science and Information Systems (CSIS), Localisation Research Centre (LRC)

The following studentships are currently available at the University of Limerick as part of a new integrated programme of research being undertaken by the Centre for Next Generation Localisation (CNGL). Within CNGL, PhD students benefit from: supervision by integrated teams of leading academics; an experienced and supportive lab community of postdoctoral researchers and research programmers; excellent collaboration and computing facilities; wide ranging skills training opportunities; a dedicated management and administration team and an active commercialisation development pipeline. For initial contact, the primary supervisors for each topic are listed below.

Content Curation Research

Content Curation Research, extracting Events and Opinions from Multilingual User Generated Content

The key objectives of this research are to extract information from raw text, in order to make this information available to later stages in the content value chain, including discovery and search, translation, personalisation, delivery and interaction as well as interoperability and analytics. This requires technologies that convert text into a “normalised” representation, such as predicate-argument structures, RDF-style triple representations, capturing named entities, relations between named entities, events, co-reference, temporal information, polarity, sentiment, subjectivity, who states a fact, holds an opinion, reacts to it, etc. One studentship is available in:

·         Multi-view Semantics for Intelligent Content Processing (supervised by J. J. Collins - J.J.Collins@ul.ie)

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Translation and Localisation Research

Translation and Localisation Research, investigating aspects of social localisation including demand- , rather than supply-driven localisation processes supported by new and emerging technologies. 

The key objectives of this research are to lead to a better understanding of and support for user-driven localisation, or social localisation. Most global digital content publishers achieve at least 60% of their overall revenue from their international business operations. Localisation facilitates this revenue stream. Without localisation, these multinational digital publishers would be very different enterprises from those they are today. The challenges of volume, variety and velocity in the production of digital content require new, dynamic technologies to provide new capabilities in localisation. At the same time, much of today’s content is demand-driven, user-generated content, rather than the traditional supply-driven enterprise-generated content.

Social Localisation supports user- and demand-driven localisation scenarios by providing a technology framework that enables the global conversation in communities that cannot be served by the current mainstream localisation model, restricted by its short-term financial return-on-investment prerogative.

In addition to its significant societal impact, this radically new ‘social localisation’ model also promotes multilingual localised content development, generation, and publication for languages and content which otherwise would be out of reach for commercial enterprises. Two studentships are available in the following, or related, areas:

·         Motivation, Quality and Control: Technologies for Social Localisation (supervised by Reinhard Schaler – Reinhard.Schaler@ul.ie)

·         Reputation Management and Multi-dimensional Clustering in Social Localisation (supervised by Reinhard Schaler – Reinhard.Schaler@ul.ie )

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Interoperability and Analytics Research

Interoperability and Analytics Research, investigating global intelligent content access, integration and standards. This includes the development of the XML-based Localisation Interface Standard (XLIFF) and the Internationalization Tag Set (ITS), with the associated development of demonstrator implementations in collaboration with other CNGL research groups and industrial partners. One studentship is available in:


·         Effective metadata for Localisation Data Interoperability (supervised by David Filip – David.Filip@ul.ie)


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