Award Type and NFQ level : RESEARCH PH.D. (10)

CAO/PAC code : MHG02 (FT), MHG03 (PT)

CAO Points :

The aim of the Structured PhD in Computer Science is to provide the student with an opportunity to carry out a significant body of research work with support from the structured module component of the programme. The programme will offer both academic modules to enhance the student's specialist knowledge, and transferable skills modules. These modules will add significantly to the PhD experience by broadening the skill base of the candidate.

The first step to applying is to identify a potential supervisor; this involves deciding on a general research area that you are interested in and then contacting a member of the department’s staff that is specialising in that area. Note that applicants should only apply for the programme after they have secured agreement from a relevant member of staff to supervise their research. More information on research in the department can be found in the Research Interests section above. 

Research postgraduates are typically (though not exclusively) funded during their research. Support varies depending on the source, but funding can include payment of fees, a salary and travel expenses. Please note that all funding programmes are highly competitive, and most are contingent on the applicant securing high marks in their primary degree.

Research students can also register to work jointly with the Department of Computer Science and one of the Maynooth University Research Institutes or Centres (see: Please see the entries for these institutes for more details of the research topics available

Closing date
Research applications are generally accepted at any time

September (or other agreed time)

Applications are invited from students who have achieved high marks in their undergraduate degree. This is typically a first-class honours in Computer Science or a closely-related discipline, although students with a second class honours primary degree can also be considered.

Applicants must have a recognised primary degree which is considered equivalent to Irish university primary degree level.

Minimum English language requirements:
Applicants for whom English is not their first language are required to demonstrate their proficiency in English in order to benefit fully from their course of study. For information about English language tests accepted and required scores, please see here. The requirements specified are applicable for both EU and International applicants..

Maynooth University's TOEFL code is 8850



Details of the research interests of the academic staff are provided below. Further information on the research activities and interests within the department is also available at:

Dr Ralf Bierig: Ralf Bierig's research surrounds the areas of human-computer interaction (including virtual reality) and information behaviour (including information retrieval and text data analysis). Here, he is focused on search behaviour, user experience, virtual reality technology, and game design. His PhD investigated the adaptive effects of personal and contextual attributes on search performance with mobile applications. He worked and published in the areas of (task-based) search behaviour with eye tracking, semantic information indexing and search, search interfaces and their evaluation, and various topics in virtual reality, including non-Euclidian navigation, usability of 3D menu interfaces, and virtual memory palaces. Other topics of interest include mindfulness to make computing applications gentler and in support of digital health and deeper forms of flow and productivity, and video game design in relation to user experience and virtual reality. He is a reviewer of the Springer Nature Journal on Virtual Reality as well as a wide range of information retrieval and HCI conferences.

Dr S. Brown: Primary research interest is in embedded networking systems: especially Wireless Sensor Networks and IoT. Also: Design and Analysis of routers/bridges for Performance and Stability, especially under overload; Engineering for Software Systems (Software Engineering) and Software Engineering Education; Embedded Operating Systems (especially support for latency, throughput, & buffering).

Dr K. Casey: Kevin Casey's main research areas are in programming language design, code optimisation, embedded devices, cloud architectures, big data, web-development frameworks and CS education. Since his PhD work in JVM interpreter optimisation, he has worked with researchers on VLEs, dataflow languages in VR, visualisation, and energy optimisation for Java virtual machines. He has also worked with industrial partners on embedded solutions, cloud architecture, efficient big-data cloud processing, agile processes and advising on development strategy. In addition, Kevin is currently a funded SFI principal investigator on CoCoA23, a multi-year project to bring computational thinking to primary and secondary schools.

Dr N. Culligan: Dr Natalie Culligan’s research interests include Computer Science Pedagogy, Data Analysis, Media and Gaming. She wrote her PhD “Two Roads Diverge: Mapping the Path of Learning for Novice Programmers Through Large Scale Interaction Data and Neural Network Classifiers” on data gathered from 1st year students as they learned to code using the pedagogical coding environment MULE (Maynooth University Learning Environment), which was developed as part of her research. Before beginning her Computer Science career, she studied Sound Engineering in Ballyfermot College of Further Education and has worked as a sound engineer in both music venues and recording studios.

Professor R. Dahyot: Research interests are in between the traditional fields of Electronic and electrical engineering (digital signal processing), Computer Science (computer vision & graphics), artificial intelligence (data mining, machine learning) and Mathematics (Statistics, Information theory). Prof Dahyot is a principal investigator with the SFI | I-Form centre on advanced manufacturing, with the ADAPT, the SFI Research Centre for AI-Driven Digital Content Technology ( and a funded investigator with the upcoming SFI Climate+ Research centre.

Dr T. Dowling: Theory and practice of cryptography and cryptanalysis. Information warfare. Java and perl based implementation of cryptographic protocol and systems. Smart card development and integration. Numerical computing. Developing computer based simulations of algebraic constructs. Theory and application of Elliptic curves over finite fields and extension fields. Performance analysis of elliptic curve algorithms. Computer forensics and network security protocols and tools.

Mr J. Duffin

Dr. B. Faghih: Behnam Faghih's primary research focus lies in music technology (computer music) in both traditional audio signal processing and machine learning approaches for working with audio, especially music. Using AI for music information retrieval (MIR), music analysis, and generating music. In addition, developing AI tools for music e-learning. Moreover, he is also interested in e-democracy, e-government, decision-making, and open government. Furthermore, he also has an research interest in e-health.

Dr E. Galvan: His primary research focus centres around bio-inspired methods, specifically evolutionary algorithms and artificial neural networks. His keen interest lies in autonomous search,  optimisation, multi-objective optimisation and neuroevolution. His practical applications span a diverse range, encompassing areas such as board and video games, software improvement, and data analysis. 

Dr W. Hao My research aims to create automated software and tools for solving challenging problems in software engineering domain. Currently, my research focuses on developing new languages and tools for verifying/testing graph/state-based models such as Cyber Physical Systems (CPS). In general, I have strong interests in formal methods, programming languages design, program synthesis, relational database and software testing. Many our work is based on using SAT/SMT solvers , those super well-engineered solvers that make it easier to create fully automated tools for program verification, complex model reasoning and more.

Dr B. Hennelly: His current research focuses on the development of optoelectronic microscopy systems for application in the area of clinical pathology. He is currently working on automated microscopy/spectroscopy systems for diagnosing early stage bladder cancer from urine samples using a combination of image processing algorithms and, holographic microscopy and Raman micro-spectroscopy.

Mr D. Kelly: Distributed Systems, the Internet and its application to the emergence of virtual societies, grid computing, e-commerce and database backed services, mobile internet services, multimedia delivery, collaborative applications, network centric games, virtual reality environments and remote monitoring and control. 

Dr L. Kelly: Applied artificial intelligence - intelligent search, ubiquitous computing, and multimodal information access and retrieval - context sensitive retrieval and evaluation methodology

Mr T. Lysaght: Digital signal processing with application to real-time audio. Sound synthesis. Computer vision.

Dr P. Maguire: Phil Maguire's main research interests are in the area of cognitive science and theoretical computer science. In particular he is interested in representation, uncertainty, standards of measurement and the foundations of mathematics, with applications to the fintech industry.

Dr C. Markham: Charles Markham is a graduate of Applied Physics at DCU. His PhD was in the area of element specific imaging in computerised tomography. He has maintained an interest in novel imaging systems, instrumentation, sensing and machine vision technologies. He has collaborated with the Engineering Department and Hamilton Institute at MU to develop a brain computer interface based on optical tomography. The work involved developing accurate methods of photometry to allow blood oxygen levels to be measured and so infer brain activity.  Working in collaboration with TU Dublin he developed novel methods of measuring and locating retro-reflective objects in sequences recorded by a custom mobile vision system. He has developed techniques for imaging using coded apertures and developed wide-baseline stereo imaging methods to achieve a visual radar system. Working with the physiotherapy department at UCD, he developed practical sensors for integration into wearable biofeedback systems and has maintained an interest in motion capture (MoCap). He has also collaborated on multidisciplinary research in the area of measuring driver behaviour and has integrated eye-tracking and EEG sensors into novel driving simulators. Currently he is developing a research interest around computer modelling of disease and invasive species.  More recently he has been working on modelling wildfires. He is an active member of the MU Mathematics and Statistics Ecology group. He teaches Robotics, Computer Graphics and Advanced Computer Architecture.

Dr A. Mooney: Aidan Mooney’s research is concerned with pedagogy and the development of tools and systems to support and enhance engaging pedagogy. His interests include large class teaching, automated assessment, timely feedback, Computational Thinking, Eye-tracking technologies, Access learning, collaborative learning and inclusive technologies. He sees technology as playing a vital role in Education and has researched and developed numerous tools to enhance student participation and learning. He has also an interest in image processing and digital watermarking.

Dr P. Mooney: Peter’s research is focused on the production, analysis, storage and dissemination of geographical/geospatial data and information (more commonly known as GeoCompation). Computer Science forms a fundamental part of this research but due to the nature of geographical data and information a multidisciplinary approach is required. He has been heavily involved with the crowdsourcing of geospatial data and information (in particular OpenStreetMap) and how this has become major social and technological driver over the past two decades. For almost two decades, Peter has been actively involved in European initiatives around Citizen Science and is involved with FOSS4G (Free and Open-Source Software for Geomatics) at national, European and global levels. More recently, his research has expanded to consider the use of Artificial Intelligence in Environmental Sustainability, Smart Cities, and the Circular Economy.

Professor R. Monahan: Rosemary's research is concerned with the development of reliable software systems, working on formal techniques for modelling, analysing and verifying software systems. She is passionate about providing solid mathematical foundations for the development of software and in applying next-generation verification technologies to generate trustworthy software systems. Recent projects concern formalising software requirements and support for traceability from initial requirements through to the implemented software system, as well as the application of deductive verifiers and model checkers to verify the correctness of these systems. She is also passionate about teaching the science of problem-solving through computational thinking and has lead projects which co-create educational resources with teachers at primary and secondary school levels.

Professor T. McCarthy: Earth Observation (EO), Global Navigation Satellite System (GNSS), Sensor technologies, Connected Mobile Devices, Cloud Platforms, Open Data, Internet of Things (IoT), Autonomous Vehicles, Unmanned Aircraft Systems (UAS) - or Drones - have ensured that geographical data continues to have a useful and important contribution to make across all sectors including; Natural Resources, Environment, Transportation, Critical Infrastructure and Emergency Management. All of these sensing technologies are capable of capturing, recording data about various static and dynamic phenomena of the world around us - usually with a very useful location-time-stamp reference. Examples include recent multispectral images of agriculture crops from Satellite sensors, GPS tracks of road vehicles, water quality or changing patterns in weather and climate. These geospatial technologies now routinely churn out Petabytes of data on a daily scale. Geographical data will remain just that if not transformed into useful information and sectoral-specific knowledge using latest Machine Learning algorithms, spatial analysis and models

Professor J. McDonald:John McDonald's research interests lie at the intersection of computer vision, robotics, and AI, focussing on the development of spatial perception and intelligence for autonomous mobile robotics. His research aims to develop systems that intrinsically understand the three-dimensional nature of the world around them, and how to move, navigate, and operate within that world. This problem is referred to as simultaneous localisation and mapping (aka SLAM) and is one of the most intensely researched topics with the field of robot perception over the past 35 years. Dr. McDonald’s group have made a number theoretical and applied contributions in the area, developing a variety of sparse and dense visual SLAM systems for both indoor and outdoor applications. More recently, the dramatic progress in AI, ML, and deep learning has seen an evolution of the problem to what is now referred to as SpatialAI, where data driven techniques are combined within this geometric pipeline of SLAM, thereby enabling semantic mapping of a robot’s environment. Here the aim is to endow robots with the capability to build a representation of their world at the level of objects and their affordances. 

Professor T. J. Naughton: Tom Naughton's research interests are broadly in the areas of computer theory, parallel computing, and optical image processing, with applications in future computing technologies, biology, health, and education. In the field of optical image processing these interests include numerical analysis and visual perception analysis of three-dimensional scenes encoded in digital holograms, rapid detection of cancer in cells using deep learning and digital holographic microscopy, optical computing to speed up learning in artificial intelligence, computational complexity analysis of analog optical computers, and lossy compression for digital holograms. Other long-standing interests include unconventional models of computation (e.g. computing with molecules), parallel computing to speed up bioinformatics algorithms, artificial intelligence applied to psychology experiments, and simple models of computation to teach computational thinking concepts to schoolchildren.

Mr M. Noone

Mark Noone’s research focuses on student retention in CS, differences between visual and textual programming languages and the development of hybrid “visual-textual” programming languages.

Dr D. O’Donoghue: Diarmuid O'Donoghue's research is focussed on computational models of how people reason with analogical comparisons. He has been focusing on geometric proportional analogies, typified by those problems found in IQ tests. These analogies take the form A:B as C:D (read as, A is to B as C is to D), with the objective being to generate D from the given information (A, B and C).

We consider analogies where each of the objects include attributes, such as colour and shading. Solutions being developed combine (isomorphic) structure mapping between parts A and C of the analogy, with an attribute matching process - resulting in a family of structure matching algorithms. These algorithms are also being applied to the domain of qualitative spatial reasoning, particularly to interpreting and enhancing topographic maps. Other areas of interest include mathematical models of the web, genetic algorithms and simulated genetic-repair operators.

Professor B. A. Pearlmutter: Prof. Pearlmutter’s primary technical interest is in systems that adapt: how to analyze them, how to understand them, how to build them. Because the most flexible and competent adaptive systems available is the nervous system, he is interested in artificial neural networks and computational neuroscience. He is most focussed on the construction of novel architectures and algorithms that enable us to understand and attack previously unassailable problems, and to understand previously mysterious aspects of nervous system function. A secondary interest of Prof. Pearlmutter’s is in programming systems, especially advanced programming language design and implementation.  One of his projects is to build a new efficient advanced programming language with novel constructs that allow many numeric algorithms and scientific computations to be expressed clearly and succinctly.

Professor R. Reilly: Ronan Reilly’s main research interests are in the areas of visual perception and language understanding.  His interest in vision research primarily relates to eye movement control in reading, which also conveniently combines a language dimension. His research in this area involves data collection using an eye tracking system, and the computational modeling of these data. More recently he has started to look at the application of my reading model to web usability analysis. Within the language area, he has a specific interest in alternatives to the currently dominant nativist accounts of language acquisition.  Again, this work is underpinned by computational modelling.

Prof. Reilly has also been working on a theoretical approach to modelling cortical computation, which he refers to as "Cortical Software Re-Use".  The goal of this theory is to try to account for the construction of cognitive capabilities within a developmental and evolutionary framework.  The main assumption of this line of research is that cognitive and linguistic capabilities are incrementally constructed from sensory-motor functions. These act as a repertoire of neural functionality that get exploited in the development of more complex neural capacities.

Dr J. Timoney: Audio signal processing with an emphasis towards multimedia applications. Of particular interest is anything connected with Music technology and sound. This includes frequency analysis, new digital effects, musical software systems, hardware platforms, interactive digital instruments, intelligent musical instruments, and algorithms for rhythmic and harmonic manipulation. In addition to this, he has broader interests in software technologies for health improvement and empowerment, digital transformations, process modelling, and machine learning applied to data analysis. 

Professor D. Woods

We are always looking for passionate, smart people who want to make meaningful scientific contributions to the world at undergraduate, Masters, PhD and postdoc levels. Our research is multidisciplinary, primarily driven by computer science ideas, but builds on Physics, Chemistry and Bioengineering. Primarily, we have three modes of working:

  1. Theoretical Computer Science (e.g. defining molecular models of computation and characterising their computational power, efficient algorithms for prediction of DNA/RNA/molecular systems, fundamentals of computing, energy efficient computation).
  2. Design of DNA computing systems and DNA nanostructures (this includes software development, efficient data structures & algorithms, geometric design at the whiteboard, brainstorming!).
  3. Wet-lab implementation of DNA computers and nanostructures (we have excellent wet-lab facilities, you don’t need any background: folks are often building systems out of DNA after a few hours or days of training).

Our work is funded by the EU (ERC, EIC) and the Irish government (SFI). See for more details on how to join our team. 






The PhD consists of 30 credits minimum / 90 credits maximum in taught modules (15 must be in generic or transferable skills and 15 in subject-specific or advanced specialist advanced modules) with the remaining 270–330 credits being allocated to the research project and thesis.

Course Duration: 4 years Full-time, 6 years Part-time

On completing a PhD in Computer Science the graduate has a number of options open to them. They can continue to build their career as a researcher in academia, for example as a Post-Doctoral researcher, or in the technology industry. They will also be attractive as an educator in all facets of the Higher Education sector.

Other possibilities include working in scientific research administration or a high-tech start-up environment. The experience and discipline gained from completing a PhD in Computer Science also can open other avenues outside of Computer Science where these skills are prized.

Prior to applying, the candidate must have identified and contacted a member of staff prepared to act as their PhD supervisor.

The formal application process is as follows:

Online application only

PAC Code
MHG02 Full-time 
MHG03 Part-time

The following information should be forwarded to PAC, 1 Courthouse Square, Galway or uploaded to your online application form:

A personal statement is required as part of the application statement online.

Certified copies of all official transcripts of results for all non-Maynooth University qualifications listed MUST accompany the application. Failure to do so will delay your application being processed. Non-Maynooth University students are asked to provide two academic references and a copy of birth certificate or valid passport.

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