Computational Engineering (M.Sc./P.Grad.Dip./P.Grad.Cert)

Overview

This programme is actually a strand of the MSc in Electronic Information Engineering. Computational Engineering has evolved to encompass all aspects of simulation and design in the Engineering disciplines. All physical simulation tools rely on algorithms developed from a knowledge of computational techniques from graphics engines to financial prediction to fluid mechanics to electric power distribution. In this course students are equipped with the knowledge to apply computational techniques in various domains e.g. Geophysical Simulation, Transportation Engineering and Cyberphysical Systems.

The course will suit engineers and scientists wanting to open up a career in computational engineering either in research or industry. Computational engineering specialists are much in demand in sectors like finance, automotive vehicle design, transport, environmental/climate analysis and renewable energies. The core modules give students a grounding in professional software design for computational products like simulators and prediction engines, as well as a superb coverage of Deep Neural Networks which has revolutionised the field of AI. Optional modules include the very popular Quantum Computing moule, Geophysical, Transportation and Cyberphysical modules. Our module in industrial video and special effects (Motion Picture Engineering) features guest speakers from around the world and caters to the video streaming industry worldwide.

Course Organisation

This M.Sc. course can be taken as either a full-time one year or part-time two to three year postgraduate course and consists of taught modules worth 60 credits and a project worth 30 credits. MSc candidates complete a substantial project and submit a report which accounts for 30 credits.

In addition to direct entry to the MSc, parallel Postgraduate Certificate, (30 ECTS), and Postgraduate Diploma (60 ECTS) entry routes are available for direct separate application. For students who successfully complete the postgraduate certificate and postgraduate diploma, there is an option to rescind these awards and apply to complete an MSc. Part-time students may follow the staged award path over 3 years of study with a possible gap of up to one year in between.

Course Content

All students (aiming for an MSc award) are required to take the following modules:

• Research Project/Dissertation (30 ECTS)

• Research Methods (5 ECTS)

• Computational Methods (10 ECTS)

• Introduction to Deep Learning (10 ECTS)

Students must select in addition, at least 20 ECTS (out of the 30 credits of optional modules) from the following Computational Strand modules:

• Cyberphysical systems and Control (10 credits - Semester 1) Dr. Harun Siljak

• Algorithms for Quantum Computing (5 credits - Semester 1) Prof Biswajit Basu

• Simulation for Geophysical Modeling (5 credits - Semester 2) Prof Biswajit Basu

• Computation for Transportation Engineering (5 credits - Semester 2) Prof Biswajit Basu

• Digital Signal Processing (5 credits - Sem 1) Dr. William Dowling

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

• Statistical Signal Processing (10 credits - Semester 1) Prof Anthony Quinn

• Speech and Audio Engineering (5 credits - Semester 1) Dr Naomi Harte

• Spatial Audio (5 credits - Semester 2) Dr. Enda Bates

• Self-Organising Systems (5 credits - Semester 1) Dr. Nicola Marchetti

• Next Generation Networks (5 credits - Semester 1) Dr. Nicola Marchetti & Dr. Marco Ruffini

• Optimisation & Control (5 credits - Semester 2) Prof Biswajit Basu

• Motion Picture Engineering (10 credits - Semester 2) Prof Anil Kokaram

• Digital Image & Video Processing (5 credits - Semester 2) Dr. François Pitié

• Micro-Electronic Circuits (5 credits - Sem 2) Dr. Justin King

• Integrated Systems Design (5 credits - Sem 2) Dr Shreejith Shanker

• Open Reconfigurable Networks (5 credits - Sem 2) Dr Shreejith Shanker

• Introduction to XR: Applications and Technologies (5 credits - Sem 2) Dr Fionnuala Conway

Career Opportunities

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.

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