A software-led masters for the age of AIoT — connected embedded systems, edge programming, data analysis and machine learning, and the security to protect it all. Designed with industry, delivered flexibly, built around a substantial applied project.
Level 9
MEng — NFQ masters award
90 credits
8 taught modules and a project
12-20 months
Full time and part time options
5 major
pathways available
We are entering an era where the boundaries between the digital and physical worlds are dissolving. Modern innovation is no longer just about building faster computers or more connected devices; it is about creating Integrated Intelligence. From the microscopic architecture of a semiconductor chip to the global reach of next-generation telecommunications, the systems we build today are the nervous system of the modern world.
The convergence of high-performance hardware, ultra-fast connectivity, and autonomous decision-making is driving the next industrial revolution. Whether it is Physical AI allowing robots to navigate the real world with human-like perception, or Semiconductor Engineering pushing beyond the limits of Moore’s Law into the More-than-Moore era, the demand for engineers who can master these complex, heterogeneous systems has never been higher.
Ireland stands as a global powerhouse in this sector, serving as a vital hub for semiconductor manufacturing, IoT research, and network innovation. To lead in this landscape, professionals must move beyond narrow specialisations and understand how hardware, light, data, and intelligence intertwine.
AWARD:
MEng, Masters Degree — NFQ Level 9
CODE:
DC883 (MECE) — Autumn & Spring entry
DURATION:
Autumn entry is 12 months full-time / 24 months part-time. Spring entry is 20 months full time.
CREDITS:
90 ECTS — 1 credit ≈ 25 hours of study
FEES:
Programme fee (not annual) — identical for Autumn & Spring entry. Postgraduate fees
ENQUIRIES:
ee.queries@dcu.ie
CHAIR:
Prof. Derek Molloy
Why Choose the MECE Programme at DCU?
The MECE programme is designed for this innovative environment. Offering the highest level of European Masters awards, it provides a highly customisable path (with a choice of up to thirty modules) that allows students to either maintain a broad technical perspective or specialise through five industry-aligned Majors:
Physical AI: Bridging the gap between machine learning and the physical world.
Internet of Things (IoT) Devices: Mastering the ecosystem from the silicon up to the network.
Data and Telecommunications Networks: Architecting the next generation of global network connectivity.
Photonic Systems: Leading the convergence of light-based sensing and electronic systems.
Semiconductor Engineering & Integrated Circuit (IC) Design: Designing the fabrication processes and high-performance analog/digital/mixed signal integrated circuits that underpin the global economy, data centers and artificial intelligence (AI).
These majors are described fully below where you can choose the path that puts you at the heart of innovation.
Established: With a wide range of modules available, there is great scope to tailor the programme to specific needs and interests in the largest and longest-running programme of its type in the country.
Flexible: Combine full-time/part-time, on-campus/remote, a choice of two starting times each year.
Modern: The course is continually kept up-to-date to reflect changing technological advances in industry and research.
Relevant: Acquire knowledge and skills that are in high demand in industry.
Rewarding: Work on a Masters project in some of the top research labs in the country.
To meet the diverse needs of the modern tech landscape, the MECE programme offers five distinct, industry-aligned majors. Your major determines which modules count as core.
Embodied Intelligence
Advanced computer vision solutions - signal processing , data analytics, feature extraction, machine learning and deep learning.
Edge devices to network ecosystem
Real time signal processing, data analysis and machine learning, connected embedded systems and network programming.
Next-generation connectivity
Next generation wireless networking, sensor networks, core internet, protocols and architectures. Network engineering and performance analysis
Optoelectronics, integrated systems & sensors
Modern electronic and photonic device production at nanometre dimensions. Semiconductor manufacturing practices, methodologies and technologies.
Silicon systems & IC design
Design and manufacturing of analog and digital Integrated circuits
Major 01
Physical AI
Physical AI treats artificial intelligence not as a cloud-based "brain in a jar," but as a body that respects the laws of physics. At its core, this field relies on connected embedded systems to act as a high-speed nervous system, ensuring decentralised edge devices in robotics or the built environment can act without the lag of a central hub. Using real-time DSP for lightning-fast reflexes and computer vision to navigate and map 3D space, machines transition from mere automation to true perception. By weaving in machine learning and "Vision-Language-Action" models, these systems make intuitive, split-second decisions that are safe and context-aware. Furthermore, Physical AI systems are often coupled with digital twins, which are sophisticated, dynamic virtual replicas of their real-world counterparts. These digital models allow for comprehensive simulation, testing, and optimisation of the physical AI's behaviour and environment before, during, and after deployment, offering invaluable insights and enhancing the system's overall safety and efficiency.
CORE MODULES - ALL 4 REQUIRED
_____________________________________________
EEN1073: Real-Time Digital Signal Processing
EEN1071: Connected Embedded Systems
EEN1072: Data Analysis & Machine Learning 2
EEN1001: Computer Vision
RECOMMENDED SUPPORTING
_____________________________________________
EEN1097: Edge Programming with C/C++ & Rust
EEN1044: Image Processing & Analysis
EEN1083: Data Analysis & Machine Learning 1
EEN1048: Mechatronic System Simulation & Control
+ Masters project · Physical AI domain
EEN1095: Electronic Engineering Project
EEN1101: Research Training & Project Planning
30 Credits - aligned to your major
Major 02
Internet of Things (IoT) Devices
This innovative Major addresses the significance of designing and networking Internet-connected embedded systems, which form the core of Cyber-Physical Systems (CPS). Uniquely, it includes a focus on Analogue IC Design, providing students with the specialised skills to create the next generation of edge IoT devices at the integrated circuit level. Graduates gain comprehensive competencies in real-time signal processing, machine learning, and network programming. Positioned at the forefront of electronic engineering, this Major offers a unique opportunity to master the IoT ecosystem from the silicon up to the network layer, meeting the demand for professionals who can manage complex connected systems.
CORE MODULES - 4 REQUIRED
_____________________________________________
EEN1073: Real-Time Digital Signal Processing
EEN1071: Connected Embedded Systems
EEN1072: Data Analysis & Machine Learning 2
EEN1004: Network Stack Implementation
EEN1104: CMOS Analogue Integrated Circuit Design
RECOMMENDED SUPPORTING - MAX OF 4
_____________________________________________
EEN1083: Data Analysis & Machine Learning 1
EEN1097: Edge Programming with C/C++ & Rust
EEN1043: Wireless / Mobile Communications
EEN1058: Network Performance
EEN1059: Security for IoT & Edge Networks
EEN1040: Bioelectronics
+ Masters project · IOT domain
EEN1095: Electronic Engineering Project
EEN1101: Research Training & Project Planning
30 Credits - aligned to your major
Major 03
Data and Telecommunications Networks
This Major provides graduates with an in-depth understanding of the key technologies and drivers for next-generation data and telecommunications systems. Graduates are equipped with the expertise to implement advanced networking protocols on devices and user equipment, including wireless, mesh, peer-to-peer, and sensor networks. By gaining expertise in overall network design and simulation, students develop a critical cross-layer understanding of network operation. There is a strong industry demand for engineers with this skill base, capable of managing the performance and architectural drivers of modern communication systems.
CORE MODULES - 4 REQUIRED
_____________________________________________
EEN1058: Network Performance
EEN1067: Photonic Devices
EEN1072: Data Analysis & Machine Learning 2
EEN1076: Photonic Applications and Technologies
EEN1078: Future Network Architectures
EEN1004: Network Stack Implementation
RECOMMENDED SUPPORTING
_____________________________________________
EEN1043: Wireless / Mobile Communications
EEN1083: Data Analysis & Machine Learning 1
EEN1054: Mathematical Techniques & Problem Solving
EEN1059: Security for IoT & Edge Networks
+ Masters project · Data and Telecomms domain
EEN1095: Electronic Engineering Project
EEN1101: Research Training & Project Planning
30 Credits - aligned to your major
Major 04
Photonic Systems
The Photonic Systems Major is designed to develop leaders in the rapidly expanding sectors of optoelectronics. As computing moves toward the convergence of multiple technologies, experts who can integrate optical and electronic functions are critical. This Major focuses on integrated systems where layers are engineered to process light, manage power, and perform sensing. Students bridge the gap between theoretical device physics and industrial reality, gaining expertise in semiconductor manufacturing and photonic applications. This prepares graduates for innovation in fields ranging from global communications and optical sensing to biophotonics, autonomous vehicles, and next-generation quantum technologies.
CORE MODULES - 4 REQUIRED
_____________________________________________
EEN1067: Photonic Devices
EEN1003: Nanoelectronics Technology
EEN1090: Semiconductor Device Manufacturing
EEN1076: Photonic Applications and Technologies
RECOMMENDED SUPPORTING - MAX OF 4
_____________________________________________
EEN1049: Solid State Electronics & Semiconductor Devices
EEN1054: Mathematical Techniques & Problem Solving
EEN1079: Energy System Decarbonisation
EEN1040: Bioelectronics
EEN1053: Introduction to Engineering Management
+ Masters project · Photonics domain
EEN1095: Electronic Engineering Project
EEN1101: Research Training & Project Planning
30 Credits - aligned to your major
Major 05
Semiconductor Engineering & Integrated Circuit (IC) Design
The Semiconductor and Integrated Circuit (IC) Design Major provides an advanced and comprehensive foundation in the architecture, design, and fabrication of modern integrated circuits and systems. As a cornerstone of the global digital economy and a key enabler of emerging technologies such as artificial intelligence and quantum computation, the semiconductor sector demands highly skilled graduates capable of operating across the full development lifecycle. This Major equips students from diverse STEM backgrounds with the expertise to progress from semiconductor device physics and fabrication through to advanced system-on-chip (SoC) design, modelling, and verification. Emphasis is placed on the integration of theoretical knowledge with practical design skills, developed through extensive use of industry-standard Electronic Design Automation (EDA) and Technology CAD (TCAD) tools, alongside state-of-the-art process design kits (PDKs). Students benefit from exposure to current industry practices through company engagement and applied project work, fostering both technical depth and professional awareness. The programme also supports the development of analytical, problem-solving, and research skills essential for innovation in a rapidly evolving field. Graduates are well prepared for careers in semiconductor design, fabrication, and electronic systems development, as well as for progression to doctoral research and leadership roles within the global microelectronics industry.
CORE MODULES - 4 REQUIRED
_____________________________________________
EEN1003: Nanoelectronics Technology
EEN1104: CMOS Analogue Integrated Circuit Design
EEN1090: Semiconductor Device Manufacturing
EEN1106: Digital IC Design
RECOMMENDED SUPPORTING
_____________________________________________
EEN1049: Solid State Electronics & Semiconductor Devices
EEN1076: Photonic Applications and Technologies
EEN1067: Photonic Devices
EEN1073: Real-Time Digital Signal Processing
+ Masters project · Semicon domain
EEN1095: Electronic Engineering Project
EEN1101: Research Training & Project Planning
30 Credits - aligned to your major
PROGRAMME STRUCTURE - DC883
8 x 7.5
taught modules credits
+
30
masters project credits
=
90 credits in total
MSc NFQ Level 9
Twelve teaching weeks, exams in December.
_______________________________________________
Project: theme selection & allocation
Thirteen teaching weeks, exams April–May.
_______________________________________________
Project: research & design plan
Independent implementation, testing and analysis with your academic supervisor.
_______________________________________________
Final portfolio assessment end August
MEng Programme - Alternative Award Options
Graduate Diploma in Electronic and Computer Engineering (no major)
• Complete any eight Level-9 7.5-Credit modules from MEng programme
Graduate Certificate in Electronic and Computer Engineering (no major)
• Complete any four Level-9 7.5-credit modules from MEng Programme
Twelve teaching weeks, exams in December.
_____________________________________________________
Level 9 modules
Thirteen teaching weeks, exams April–May.
_____________________________________________________
Level 9 modules
A Primary Honours degree (Level 8) with an award of H2.2 or higher in Electronic/Electrical/Computer Engineering, Applied Physics, Computer Sciences or other Engineering disciplines.
International, non-native English speakers must satisfy the University of their competency in the English language — see DCU's English language requirements
Full-time students can apply directly to the University. Fees information for this programme may be found here.
Part-time students can apply directly to the University
ENTRY REQUIREMENTS
Fees: Postgraduate Student Fees Please note that merit scholarships are available for this the MSc in Electronic and Computer Technology programme.
Please also note that a programme fee is applied rather than an annual fee. Therefore, the cost is consistent for the Autumn (September) and Spring (January) entries, regardless of whether the programme is 12-months or 20-months in duration.
Talk to the programme chair, Prof. Derek Molloy — derek.molloy@dcu.ie — or the school office at ee.queries@dcu.ie.
Dublin City University
Glasnevin
Dublin 9