Program Overview

---

Queen's University Belfast

Overview

Queen's University Belfast is a public research university in Belfast, Northern Ireland. The university offers a wide range of undergraduate and postgraduate programs across various disciplines.

Study

Undergraduate

• Undergraduate programs are available in various fields, including arts, humanities, social sciences, engineering, and natural sciences.
• Students can choose from a range of courses, including single honors, joint honors, and major/minor combinations.

Postgraduate

• Postgraduate programs are available in various fields, including arts, humanities, social sciences, engineering, and natural sciences.
• Students can choose from a range of courses, including master's, doctoral, and postgraduate diploma programs.

International Students

• Queen's University Belfast welcomes international students from around the world.
• The university offers a range of support services for international students, including language support, academic support, and cultural adaptation.

Fees and Funding

• Tuition fees vary depending on the program and student status (home, EU, or international).
• The university offers a range of scholarships and funding opportunities for undergraduate and postgraduate students.

Research

Research Themes

• Queen's University Belfast has a strong research focus, with research themes including:
  • Arts, Humanities, and Social Sciences
  • Engineering and Physical Sciences
  • Life and Health Sciences
  • Natural and Built Environment

Research Areas

• The university has a range of research areas, including:
  • Advanced Materials and Manufacturing
  • Cancer Research
  • Cyber Security
  • Data Science
  • Energy and Environment
  • Food Security
  • Global Health
  • Neuroscience
  • Public Health

Research Excellence Framework

• Queen's University Belfast has a strong research profile, with 75% of its research classified as world-leading or internationally excellent in the Research Excellence Framework (REF) 2014.

Research Strategy

• The university's research strategy focuses on:
  • Interdisciplinary research
  • Collaboration with industry and external partners
  • Translation of research into impact

Research Impact

• Queen's University Belfast has a strong track record of research impact, with research contributing to:
  • Economic growth
  • Social welfare
  • Environmental sustainability
  • Cultural enrichment

International

International Students

• Queen's University Belfast welcomes international students from around the world.
• The university offers a range of support services for international students, including language support, academic support, and cultural adaptation.

Applying to Queen's

• International students can apply to Queen's University Belfast through the university's online application portal.
• Applicants must meet the university's English language requirements and academic entry requirements.

English Language Requirements

• The university requires international students to demonstrate proficiency in English language, with a minimum IELTS score of 6.0 or equivalent.

Tuition Fees

• Tuition fees vary depending on the program and student status (home, EU, or international).

International Scholarships

• The university offers a range of scholarships for international students, including the Queen's University Belfast International Scholarship.

Business

Commercialisation

• Queen's University Belfast has a strong focus on commercialisation, with a range of initiatives to support the translation of research into impact.

Partnering with Industry

• The university partners with industry to support research and development, innovation, and entrepreneurship.

Knowledge Transfer Partnerships

• Queen's University Belfast has a range of knowledge transfer partnerships with industry, including the Knowledge Transfer Partnership (KTP) scheme.

IP and Innovation

• The university has a strong focus on intellectual property and innovation, with a range of initiatives to support the development of new ideas and products.

Business Support

• Queen's University Belfast offers a range of business support services, including business incubation, acceleration, and mentoring.

About

Campus and Facilities

• Queen's University Belfast has a range of campus facilities, including libraries, laboratories, and recreational facilities.

Sustainability

• The university has a strong focus on sustainability, with a range of initiatives to reduce its environmental impact.

Social Charter

• Queen's University Belfast has a social charter that outlines its commitment to social responsibility and community engagement.

Public Engagement

• The university has a strong focus on public engagement, with a range of initiatives to support the dissemination of research and knowledge to the wider community.

Visit Us

• Queen's University Belfast welcomes visitors to its campus, with a range of events and activities throughout the year.

News

• The university has a range of news and media outlets, including the Queen's University Belfast News website.

What's On

• Queen's University Belfast has a range of events and activities throughout the year, including concerts, exhibitions, and public lectures.

Leadership and Structure

• The university has a range of leadership and governance structures, including the University Council and the Senate.

Strategy 2030

• Queen's University Belfast has a strategic plan, Strategy 2030, that outlines its vision and goals for the next decade.

Faculties and Schools

• The university has a range of faculties and schools, including the Faculty of Arts, Humanities and Social Sciences, the Faculty of Engineering and Physical Sciences, and the Faculty of Life and Health Sciences.

Professional Services

• Queen's University Belfast has a range of professional services, including the Directorate of Academic and Student Affairs, the Directorate of Finance, and the Directorate of Human Resources.

University Department List

• The university has a range of departments, including the Department of Accounting, the Department of Economics, and the Department of Law.

Rankings and Reputation

• Queen's University Belfast has a strong reputation, with a range of rankings and awards, including:
  • Ranked 173rd in the QS World University Rankings 2022
  • Ranked 201-250 in the Times Higher Education World University Rankings 2022
  • Ranked 401-500 in the Academic Ranking of World Universities 2022

Electronics with Professional Internship

Overview

The MSc in Electronics with Professional Internship is a postgraduate program that provides students with the opportunity to deepen their understanding and develop specialist expertise in a range of advanced electronics subjects.

Course Structure

• The program is available on a full-time or part-time basis.
• Students take six taught modules and complete an individual research project.

Core Modules

• Microelectronics Devices and Technology
• Project

Optional Modules

• Control and Estimation Theory
• Wireless Sensor Systems
• Wireless Communications
• Intelligent Systems and Control
• Digital Signal Processing

Professional Internship

• The professional internship is a compulsory part of the program.
• Students complete a 9-12 month internship with an industrial partner.

Learning Outcomes

• Comprehensive teaching of natural science and engineering aspects of microelectronics and application to the solution of complex problems.
• Analysis of complex problems using first principles of natural science and engineering aspects of microelectronics.
• Application of appropriate analytical techniques to model complex problems.
• Selection and application of appropriate semiconductor and associated materials and microfabrication processes.

Skills

• Assimilation of lecture material.
• Application to microelectronics device design and fabrication process design.
• Ability to apply general principles and design or analytical techniques to the solution of engineering problems.

Assessment

• Coursework (30%)
• Examination (70%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8084

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Core

Project

Overview

• The project involves the application of engineering design techniques to a topic of electrical and electronic engineering.
• Students complete an individual research project and write a dissertation.

Learning Outcomes

• All projects require a solid understanding of the associated engineering context, underlying scientific principles and methodology.
• Most projects require a solid understanding of mathematical methods, including statistics and probability.
• Some projects require a systems approach to solve engineering problems, including following a multi/inter-disciplinary approach.
• Projects are of research nature, involving developing new technologies or discovering/testing the properties or limitation of existing ones.

Skills

• Ability to apply general principles and design or analytical techniques to the solution of engineering problems.
• Ability to design novel engineering systems, proofs of concept, and demonstrate them using prototypes (hardware and/or software).

Assessment

• Coursework (85%)
• Examination (0%)
• Practical (15%)

Credits

• 60

Module Code

• ELE8060

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Core

MEMS Devices & Technology

Overview

• The module covers devices and technology for microelectromechanical systems (MEMS).
• Topics include design of MEMS sensors, sensing methods, MEMS actuators, fabrication technology, and reliability issues.

Learning Outcomes

• Knowledge of the world of microelectromechanical devices and systems (MEMS).
• An awareness of material properties, fabrication technologies, basic device structures, sensing and actuation principles.
• Ability to calculate key process and device performance parameters.
• Ability to design MEMS devices.

Skills

• Ability to design MEMS devices.
• Calculation of key process and device performance parameters.

Assessment

• Coursework (40%)
• Examination (60%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8083

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Core

Control and Estimation Theory

Overview

• The module focuses on multiple-input multiple-output (MIMO) discrete-time, linear and nonlinear systems with imperfect state information.
• Topics include dynamic programming, Lyapunov's theorem, and Bayesian estimation.

Learning Outcomes

• Demonstrate a good understanding of the notions of invariance, controllability, observability, attractivity, and stability.
• Demonstrate a thorough understanding of the principles of dynamic programming and use dynamic programming to derive the gain and optimal cost associated with the linear-quadratic regulator (LQR).
• Understand the principles underlying model predictive control (MPC) and design and implement stabilising MPC for discrete-time constrained linear and nonlinear systems.

Skills

• In this module, the students will develop the following skills:
  • Reasoning using high-level abstract concepts of systems and control theory to address today's engineering challenges.
  • Development of an analytical and statistical/Bayesian thinking.
  • Problem solving, troubleshooting, debugging (through labs and coursework).
  • Collaboration and project management (group coursework).
  • Programming skills (Python programming).

Assessment

• Coursework (60%)
• Examination (40%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8088

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Optional

Wireless Sensor Systems

Overview

• The module covers key building blocks and essentials in wireless sensor systems.
• Topics include protocols at layer 2 (MAC layer) and layer 3 (routing), power management, synchronization, and sensor technology.

Learning Outcomes

• Apply knowledge of mathematics for: Throughput and delay calculations, time synchronization, power consumption calculations.
• Apply knowledge of statistics to a broadly defined problem (sensor data sets and time series from pollutant data).
• Analyse the suitability of existing wireless technologies to support Internet of Things.

Skills

• The ability to critically assess and design modern wireless communications systems and in particular wireless sensor networks and systems.
• The ability to understand existing sensors, system architectures, communication protocols, and standards in such a context.
• Use software, statistics, and mathematical techniques for sensor data analysis and forecasting.

Assessment

• Coursework (40%)
• Examination (60%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8096

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Optional

Wireless Communications

Overview

• The module develops the necessary concepts required to understand the technology behind present-day wireless systems and sensors.
• Topics include physical wireless layer technology, transmitter and receiver architectures, antennas, modulation and demodulation, signal-to-noise ratio (SNR), and frequency selective and flat fading channels.

Learning Outcomes

• Demonstrate a good understanding of the physical hardware technology for radio wave propagation, including transmitter and receiver architectures, and the associated antenna architectures and modulation techniques forming wireless systems.
• Understand fading and the need for statistical approaches to modelling signal propagation and reception in wireless systems.

Skills

• Assimilation of lecture material, python skills, system model, and problem-solving skills as well as the application of probability, statistics, electromagnetic theory, and time-series forecasting to wireless data sets.

Assessment

• Coursework (20%)
• Examination (80%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8078

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Optional

Intelligent Systems and Control

Overview

• The module develops a robust understanding of the major academic topics which define control methods and intelligent algorithms in dynamic systems.
• Topics include software simulation of dynamical systems, state-space modelling and analysis, control design methods, state observer design, stability analysis, and introduction to advanced control methods.

Learning Outcomes

• Apply analytical methods to derive dynamic models.
• Analyse system properties in state space (e.g., controllability, observability, stability etc).
• Convert from state-space (SS) to linear transfer function (LTF) representation and vice versa.

Skills

• The module will give you experience of how to model, simulate and analyse linear and non-linear systems using software tools (e.g., Matlab), knowledge of linear state-space methods and how to apply them to model, analyse and design control laws for dynamical systems, and knowledge of a range of intelligent systems techniques and how to apply them to solve practical engineering problems.

Assessment

• Coursework (40%)
• Examination (60%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8066

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Optional

Digital Signal Processing

Overview

• The module covers signals and spectral representation, linear systems, Fourier and Laplace transform, convolution, impulse response, transfer function, sampled data, sampling theorem, design of analogue filters, infinite impulse response (IIR) filters, finite impulse response (FIR) filters, truncation and windowing.

Learning Outcomes

• Application of elementary algebra, complex number theory, linear algebra, statistics, and calculus in the derivation and analysis of signal processing systems and algorithms.
• Digital IIR and FIR ideal filter design requires derivation (applying various maths techniques) of coefficients from given filter requirement data, considering application-related constraints on the global filter characteristics.

Skills

• numeric
• problem solving
• design, implement and test digital filter designs in Matlab
• perform spectral analysis on signals

Assessment

• Coursework (40%)
• Examination (60%)
• Practical (0%)

Credits

• 20

Module Code

• ELE8059

Teaching Period

• Full Year

Duration

• 24 weeks

Pre-requisite

• No

Core/Optional

• Optional

Professional Internship

Overview

• The Professional Internship is a compulsory part of the academic program.
• Students complete a 9-12 month internship with an industrial partner.

Learning Outcomes

• The overall aim of the professional internship is to provide the student with experience in industry which complements the academic study in the University and contributes to their development.
• Precise objectives to achieve this aim vary from placement to placement.
• Ideally, the students should:
  • Understand the operation of industrial, commercial or government service organisations.
  • Understand the systems of communication, control and responsibility within the organisation.
  • Acquire experience of working with other people at all levels.
  • Have an appreciation of the organisational and administrative principles of running a business.
  • Further develop their personal communication skills; good use of language, accurate writing and appropriate style and manner are required.
  • Learn how they can best contribute to the organisation and develop their potential and self-management; appropriate application of initiative should be encouraged.
  • Acquire confidence in applying their knowledge to the solution of real problems; in keeping with this, they should be given progressively increasing responsibility.

Skills

• Applicants have the opportunity to complete a professional internship of up to 12 months as part of their studies on this course.
• Using the schools’ links to numerous related companies, many with international connections, students will be encouraged to apply and supported through the process.

Assessment

• Coursework (100%)
• Examination (0%)
• Practical (0%)

Credits

• 0

Module Code

• ELE8087

Teaching Period

• Full Year

Duration

• 36 weeks

Pre-requisite

• No

Core/Optional

• Core