Engineering - Electronic Information Engineering

Course Information:

This is a one year full time or two year part-time postgraduate course designed to provide graduate engineers with specialist understanding of modern computational products and systems. There is no aspect of modern life that is not now altered by information processing engines. Examples include digital assistants (speech recognition and synthesis), automotive (remote sensing and electronic control systems), the economy (quantitative automated trading), entertainment (audiovideo streaming and cinema visual effects), health (medical imaging), science (computational biology/geography/chemistry/photography) and the digital humanities. The principles enabling the design of this new wave of products are embodied in the discipline of Information Engineering. This course allows graduates to specialise in fundamental theory and applications relating to the generation, distribution, analysis and use of information in engineering and science.

Course Organisation

This M.Sc. course is a full-time one year postgraduate course and consists of taught modules and a project amounting to 90 credits. The taught component comprises modules totalling 50 credits. In the first semester, students pursuing the course must take modules worth at least 25 credits, and in the second semester they take the balance of the credits. M.Sc. candidates will, in addition, complete a substantial research project and submit a dissertation which accounts for a further 40 credits to be eligible for consideration for the award of the degree.

Entry requirements

Special Entry Requirements

Admission is normally restricted to graduates who have achieved an upper second class honours degree (2.1), or better, in engineering, science, computing, statistics, mathematics or a related discipline. Well-qualified candidates or industry professionals from other numerate disciplines who have sufficient knowledge of computational aspects of engineering and science, may also be considered for admissions purposes subject to the decision of the Dean of Graduate Studies. We will also accept official MOOC certification from reputed online sources e.g. Coursera, eDX, the IET, the IEEE in relevant numerate topics as appropriate demonstration of pre-requisite knowledge.


1 year full-time.

Further enquiries

Course Coordinator: Professor Anil Kokaram

Telephone Number: +353-1-896 2508

Course Email:

Subjects taught

All candidates are required to take the following module(s):

• Research Project/Dissertation (40 credits)

• Research Methods (15 credits)

• Statistical Signal Processing (5 credits)

• Introduction to Deep Learning (10 credits)

In addition, candidates select a further 20 credits from the following list to bring their total credits to 90:

• Speech and Audio Engineering (5 credits)

• Spatial Audio (5 credits)

• Audio Production Engineering (5 credits)

• Digital Media Systems (10 credits)

• Wireless Networks and Communications (5 credits)

• Complex Systems Science (5 credits)

• Reconfigurable Hardware for Computational Engineering (10 credits)

Some of the module options in either semester may be withdrawn from time to time and some new modules may be added, subject to demand.

Assessment method

The pass mark for all elements is 50%. To qualify for the award of the M.Sc. degree, students must achieve an overall average mark of at least 50%, achieve a pass mark in the dissertation and either (i) pass taught modules amounting to 60 ECTS credits or (ii) pass taught modules amounting to at least 50 ECTS credits and have a mark of not less than 40% in the failed modules. Both examination and dissertation are subject to external moderation.

Those students who achieve an overall average mark of 70% or above both for the course and in the dissertation will be awarded a distinction. A distinction cannot be awarded if a candidate has failed any module during the course.

Application date

Closing Date 30 June 2020

Enrolment and start dates

Next Intake: September 2020

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