Computer Science & Statistics - Research

School Description:
The School of Computer Science and Statistics has a very active Ph.D. programme, with about 200 students currently enrolled. The objective of the programme is that its Ph.D. students undertake world-class research that will have a demonstrable impact on society at large and, in so doing, to have trained the researchers and academics of the future.

Entry requirements

Applicants must normally have an excellent primary degree, and / or professional qualification, in a relevant discipline from a reputable institution. In addition, PhD applicants should have an excellent Masters degree from a reputable institution. All applicants must have a fluent command of the English language. Since the demand for places is extremely high, these minimum requirements do not guarantee admission. Preference is given to the strongest academic applicants.

Enrolment dates

March 2020 Entry

Doctor in Philosophy, Computer Science (Part-Time)
Doctor in Philosophy, Computer Science (Full-Time)
Doctor in Philosophy, Statistics (Part-Time)
Doctor in Philosophy, Statistics (Full-Time)
Master in Science, Computer Science (Part-Time)
Master in Science, Computer Science (Full-Time)
Master in Science, Statistics (Part-Time)
Master in Science, Statistics (Full-Time)

September 2020 Entry

Doctor in Philosophy, Computer Science (Part-Time)
Doctor in Philosophy, Computer Science (Full-Time)
Doctor in Philosophy, Statistics (Part-Time)
Doctor in Philosophy, Statistics (Full-Time)
Master in Science, Computer Science (Part-Time)
Master in Science, Computer Science (Full-Time)
Master in Science, Statistics (Part-Time)
Master in Science, Statistics (Full-Time)

Research

School Description:

The School of Computer Science and Statistics has a very active Ph.D. programme, with about 200 students currently enrolled. The objective of the programme is that its Ph.D. students undertake world-class research that will have a demonstrable impact on society at large and, in so doing, to have trained the researchers and academics of the future.

Current research areas in the School

Computer Science:
Current research in computer science covers a wide range of topics from the theoretical to the applied. Much of this research is funded by the EU, national funding agencies such as Science Foundation Ireland and the Higher Education Authority as well as both indigenous and multinational companies. Staff research interests include: distributed systems including middleware and ubiquitous computing, artificial intelligence, especially logic programming, neural networks and case-based reasoning, cognitive science, computational linguistics, natural language processing, computer vision and robotics, image processing, networks and telecommunications including network management, security, electronic commerce and mobile communications, computer architecture, grid computing, multimedia servers, computer graphics, image synthesis and animation, virtual reality, multimedia systems, information systems and management, management of ICT, health informatics, and formal methods.

Statistics:
The Statistics Discipline has one of the most active research groups in this field in Ireland. The research interests of its staff and graduate students include: modern computationally intensive tools in both Bayesian and classical statistics (techniques which are driven by new applications in science and engineering), theoretical work on modern regression methods, and specialist applications of statistics in business, industry and society. Projects currently supporting research students under funding from national and international agencies include: Bayesian statistical computation using functional approximations like Laplace and variational Bayes, palaeoclimate reconstruction, source separation for multi-spectral astronomical images, estimating species diversity in marine animals, failure and reliability of complex telecommunications networks and optimal road traffic management.

More details
  • Qualification letters

    MSc PhD

  • Qualifications

    Degree - Doctoral (Level 10 NFQ)

  • Attendance type

    Daytime

  • Apply to

    Course provider