The Electronic Engineering Department offers a structured Research Masters programme in Electronic Engineering. The objective of this programme is to produce high quality graduates with the skills and advanced engineering knowledge to operate as independent researchers and take on leadership roles in research and development both in academia and in industry. Our structured approach to postgraduate education provides students with an excellent foundation in a variety of technical areas that are targeted towards the research area of the student combined with training in research, communication and business skills. We will also encourage engagement with the global research community, in academia and industry, through research visits, internships and attending conferences.
Research applications are generally accepted at any time
September (or other agreed time)
All candidates should have obtained a 2.1 in Electronic Engineering, Computer Science or a degree in a related area. Applicants may be required to attend for interview as part of the admissions process. Applicants must have a recognised primary degree which is considered equivalent to Irish university primary degree level.
A full list of research areas available in the Department https://www.maynoothuniversity.ie/electronic-engineering/our-research.
If you are looking for a specific topic area, please contact the researcher closest to your interest area. All our researchers are open to discussing potential research topics. Our general areas include:
- Analysis of Dynamic Systems
- Machine learning and Data Based Modelling
- Wireless systems (telecommunications)
- Renewable energy (focus on wave energy systems)
- Neural Systems & Rehabilitation Engineering
- Biomedical engineering
- Control systems
- Sound and Speech Signal Processing
- Microelectronic circuits
Individual staff research interests:
Prof John Ringwood
Modelling and advanced control of industrial, environmental and biomedical processes. Particular focus on ocean energy systems, with modelling, control, estimation and forecasting application. Biomedical analysis includes analysis of feedback systems in physiology and non-invasive methods for measurement of anaerobic threshold in athletes.
Dr Seán Doherty
Modelling and advanced control of non-linear chemical processes, particularly pH. Artificial Neural Networks for modeling of dynamic non-linear systems. Multivariate Statistical Process Control and its application to process diagnostics and quality control.
Dr Rudi Villing
Intelligent systems, Signals and embedded software with application to autonomous robotics and devices for health and well being.
Prof. Ronan Farrell
Radio technologies for 5G, marine and aerospace communications
Sensor Networks and the Internet of things
Uses and Impacts of Mobile Communications.
Dr Bob Lawlor
Audio digital signal processing.
Biomedical signal processing.
Audio time-scale and frequency scale modification.
Sound Source Separation.
Dr Seamus McLoone
Modelling from Data – Linear and non-linear system identification techniques applied to dynamical system modelling, time series prediction and signal processing.
Intelligent Systems Engineering – Utilising AI techniques such as Fuzzy Logic and Multiple Models to solve engineering problems.
Improving the student learning experience – Investigating different styles of teaching and assessment to provide a better education for students.
Integrating technology into the classroom environment.
Dr. John Dooley
- Digital compensation techniques for high efficiency RF power amplifiers
- Cellular network level power efficiency optimization
- Distributed PAs for Massive MIMO and Beamforming
- Ku and Ka band satellite communications
- E-band wireless communications system design, build and testing
- Industry led validation of research projects
Dr. Bryan Hennelly
- Optical engineering and opto-electronics.
- Quantitative phase imaging and computational imaging for 3D imaging of biological cells with applications to clinical cytology.
- Interferometry and image processing for metrology
- Designing and building advanced microscopy systems for biological applications.
- Laser based spectroscopy for clinical diagnostics.
- Biophotonics; the application of light to understanding biology.
For further information on research in Electronic Engineering see https://www.maynoothuniversity.ie/electronic-engineering/our-research.
Students complete a thesis on a significant body of research and take a minimum of 10 credits in taught modules from the Structured MSc programme. (at least 5 in generic/transferable modules and at least 5 in subject specific/advanced specialist modules)
Modules can be completed at any stage of the programme. Students must complete a module in the semester they wish to be assessed. Each module can only be taken once in the programme and credit cannot be achieved for completing the same material in 2 different modules.
Online application only http://www.pac.ie/maynoothuniversity
All applicants to Research programmes must contact the Academic they wish to work with before applying to PAC. Please see the ‘Research Interests’ section for a list of academic staff and specialisms within the Department.
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 process. 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.
Applicants may be required to attend for interview as part of the admissions process.