Electronic Information Engineering (M.Sc. / P.Grad.Dip / P.Grad.Cert.)

Course Overview

We are in the next Industrial revolution and the challenge faced by graduates is to succeed in an age of automation. There is no aspect of modern life that is now not altered by information processing engines. Examples include teaching (online learning and assessment), automotive (driverless cars and electronic control systems), the economy (high-speed automated trading), entertainment and shopping (virtual assistants and recommendation engines), health (automated diagnostics and non-invasive body scanning) and the digital humanities.

The principles enabling the design of this new wave of products are embodied in the discipline of Information Engineering.

This 1-year full-time or 2 to 3-year part-time postgraduate course is designed to provide graduate engineers with skills to design modern computational products and systems. Graduates specialise in fundamental theory and applications relating to the generation, distribution, analysis and use of information in engineering and science.

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.

English Language Requirements

All applicants to Trinity are required to provide official evidence of proficiency in the English language. Applicants to this course are required to meet Band B (Standard Entry) English language requirements. For more details of qualifications that meet Band B, see the English Language Requirements page here.

While some of our students choose to pursue PhD degrees from leading international universities, most of our graduates choose to enter the job market. They have gained employment in various industries, including digital assistive technology (speech recognition and synthesis), automotive systems (remote sensing and cyber-physical control), economics (quantitative automated trading), entertainment (audio-video streaming and cinema visual effects), health (medical imaging) and computational science and engineering.