| Application Date |
Expand+How to Make an Application
To make an application, please use the application portal. Before making an application, please ensure you have all appropriate entry requirements and provide all supporting documentation.
DCU Student Application Por...
Hide-How to Make an Application
To make an application, please use the application portal. Before making an application, please ensure you have all appropriate entry requirements and provide all supporting documentation.
DCU Student Application Portal
DCU Student Application Portal Access
DCU Student Application Portal Guide
Important Note:
Before making a research application, the applicant must consult and seek approval from the School regarding the proposed programme of study. Additional information for research applicants is also available on the DCU Graduate Studies page.
Closing Dates
There are no closing dates for the majority of Postgraduate Research applicants (although this may be subject to change). Deadlines can apply for professional doctorate programmes, e.g. Doctor of Psychotherapy, Doctor of Education, Doctor of Elite Performance (Sport).
See the relevant Research section on School pages for more information.
Outcome of an Application
Candidates who submit a valid application for DCU will be notified of the outcome of their application by email. As such, it is important to ensure that your address for correspondence is accurate and current. Please allow 4 - 6 weeks for your application to be processed.
|
| Entry Requirements |
Expand+To register for a Postgraduate Research programme, a candidate must normally have obtained a primary degree classification equivalent to Lower Second Class Honours or above, from an approved University or an approved equivalent degree-awarding body, ...
Hide-To register for a Postgraduate Research programme, a candidate must normally have obtained a primary degree classification equivalent to Lower Second Class Honours or above, from an approved University or an approved equivalent degree-awarding body, or have an approved equivalent professional qualification in an area cognate to the proposed research topic.
PhD: Candidates holding an appropriate Master's degree obtained by research may apply for direct entry to the PhD register to conduct research in a cognate area.
PhD-track: Candidates with a taught Master's degree in an appropriate discipline with first- or second-class honours, and candidates with a primary degree in an appropriate discipline with first- or second-class honours, grade one, may apply and be considered for entry to the PhD-track register with a view to proceeding towards a PhD. Such candidates will undergo a confirmation procedure, as outlined in the Academic Regulations, before being admitted to the PhD register.
Master's by Research: Candidates holding a primary degree equivalent to a second-class honours, grade two, may apply for entry on the research Master's register. Students on the Master's register may apply for transfer to the PhD Register under the same conditions, and using the same procedure, as PhD-track candidates requesting confirmation on the PhD register.
English Language Requirements can be reviewed at:
https://www.dcu.ie/registry/english-language-requirements-non-native-speakers-english-registry
Applicants are assessed and ranked based on their performance at university, and the details provided on their application. Candidates may be called for interview and/or assessed on the basis of written work/proposed area of research.
|
| Research Areas |
Expand+Database/Ontologies
Research in this area explores efficient storage, retrieval, analysis, and visualization of data for analysis and pattern discovery. This encompasses a wide range of topics including improved indexing and query languages, data co...
Hide-Database/Ontologies
Research in this area explores efficient storage, retrieval, analysis, and visualization of data for analysis and pattern discovery. This encompasses a wide range of topics including improved indexing and query languages, data compression, multimedia storage and retrieval, data clustering, pattern matching, and high-dimensional data modelling.
Software Engineering
Research in this area focuses on the design of new formalisms and frameworks to improve the quality of software. Software is a solution to a computational problem using a formal programming language. The constructs of the language and the tools available to model, implement, and test a software system influence the quality of that solution, in terms of correctness, reliability, readability, computational efficiency, and efficiency in design and development.
At the linguistic level, research focuses on constructing methods for extending existing languages with domain specific features, for example, and in exploiting logic and type theory based approaches in developing flexible and secure programs. At the implementation level, our work focuses on designing virtual machines and compilation techniques to support extensibility and to realize new and sophisticated programming language features.
Data Science
Our expertise spans the full data science life-cycle: from information management and privacy, via machine learning and representational logics, to practical applications in bio-health informatics.
A key feature of our approach is closely coupling methodology and application. This creates a self-fulfilling loop, where challenging real-world problems drive the methodology research agenda, but also provide a natural route to exploiting new algorithms and methods.
Security & Encryption
Security and Encryption has been one of our top research interests for years, alongside related topics like safety and data privacy. This theme encompasses cybersecurity, protocol analysis, systems security, trusted computing, human-centred security, and networking.
Human Computer Interaction
Research in this area focuses on developing more effective methods for humans to interact with and use computer technology. HCI draws from computer science, sociology, and psychology to create better interfaces, to improve human-human interactions, and to tailor computer technology to the needs of an individual or organization.
The department's HCI group specializes in interfaces that help groups of people work together more effectively. Research efforts include developing algorithms and interfaces for handheld devices to aid coordination in space and time, and in applying social science theories from economics and social psychology to the development of community Web sites. The group also specializes in recommender systems with a long history in the development and analysis of algorithms, interfaces, and user applications.
Information Management & Retrieval
In the last 15 years’ web search engines have become pervasive and search has become integrated into the fabric of desktop and mobile operating systems. Prior to this, IR systems were found in commercial and intelligence application. As with many computer technologies, the capabilities of retrieval systems grew with increases in processor speed and storage capacity. The development of such systems also reflects a rapid progression away from manual library-based approaches of acquiring, indexing, and searching information to increasingly automated methods.
With the growth of digitised unstructured information and, via high speed networks, rapid global access to enormous quantities of that information, the only viable solution to finding relevant items from these large text databases was search, and IR systems became ubiquitous.
Artificial Intelligence
Artificial Intelligence (AI) is concerned with getting computers to perform tasks that currently are only feasible for humans. Within AI, Machine Learning aims to build computers that can learn how to make decisions or carry out tasks without being explicitly told how to do so. We conduct innovative research in all areas of Artificial Intelligence, including:
Machine Learning
Deep Neural Nets
Deep Learning
Natural Language Processing (see Computational Linguistics Group)
Semantics, Ontologies and Reasoning
Multi-Agent Systems
Recommender Systems
Language processing
The Language Processing group has a long tradition of basic and applied research in Natural Language Processing (NLP), the aim of which is to develop robust systems for analysing and generating human language. We specialise in the following areas:
Evaluation of NLP systems
Irish Language Technology
Language Generation
Machine Translation
Neural Network Interpretability
Question Answering and Machine Reading Comprehension
Sentiment Analysis
Syntactic Analysis and Treebanking
Ed Tech
The Ed Tech research theme is concerned with the use of software tools to support the learning and teaching process. The primary focus of this research is upon practical tools that can be applied in teaching at university level. Complementary research is addressing conceptual issues concerned with the development of computer-based learning environments for general educational applications.
Current work is concerned with software tools and principles in the areas of peer assessment, plagiarism detection, and automated submission and assessment systems. Other projects include the development of agent-based pedagogic architectures, and the use of learning objects in educational software.
Other research within the group has been directed towards principles for the development of interactive learning environments. A significant theme in this work is that the choice of programming paradigm strongly influences the support that the computer can give to constructionist approaches to learning.
Content Analytics
Content analytics defines a family of technologies that processes digital content and user behaviour in consuming and engaging with content, such as documents, news sites, customer conversations (both audio and text), and social network discussions, to answer specific questions.
Sustainable Technologies
If we choose to view the future as a better place than today, the technologies we create must be sustainable, i.e. their use will not compromise our better future.
Sustainable technologies underpin a better future for humanity; these technologies can be categorised as contributing to:
Environmental sustainability, i.e. sustainable use of energy and Earth's resources.
Economic sustainability, i.e. a stable and healthy economy.
Social sustainability, i.e. a stable and healthy society.
The School of Computing's Sustainable Technologies theme covers work happening in the School in areas including energy and the social impact of technology.
|