MSc Degree Programme:
Our Signal Processing and Communciations MSc programme was established in September 2004 and, since then, over 520 students from around 30 different countries have graduated from the programme. The School is one of the most industrially engaged in the University, with graduates providing a strong economic impact when they enter the workplace.
Signal processing and communications provide the theoretical foundations for any application which generates, processes, transmits or stores any type of signal. Practical examples are computers and smart phones, and the Internet, UHD Blu-ray players and video streaming, autonomous vehicles, wearable sensors, human-computer interfaces (HCI), radar and wireless systems, sensor networks, medical images, digital cameras, financial products, and many more. Signal processing and communications are key areas underpinning the Internet of Things and machine learning revolutions we are experiencing today.
"Answer real-world problems and create your future in the digital technology industry with our MSc in Signal Processing and Communications".
This course is one of several in Europe which has a curriculum that covers both signal processing and communications, with a strong emphasis on machine learning techniques. The key strength of our course is that we place an emphasis on fundamental concepts and how they relate to recent advances in both disciplines. We also use real-world system examples to demonstrate their practical application. The MSc project provides an exciting opportunity to work on state-of-the-art research topics.
Academic staff who teach on the MSc Signal Processing and Communications programme are at the leading edge of some of the most exciting advances in Signal Processing, Communications, and Machine learning research. As part of the Electronics and Electrical Engineering discipline at Edinburgh, we have been awarded very high ratings for both teaching and research.
SPC Class Photo, 2018-19 (Taken August 2019)
“The most precious thing I obtained from this MSc course was the motivation and passion to study interesting problems in signal processing and communications, looking at familiar concepts from new perspectives, and discovering and solving novel challenges along the way. This was done by being lectured difficult concepts with clarity, solidifying them through practical exercises, and generalizing them in the context of real research problems. The MSc coverage of emerging and challenging topics of modern signal processing helped me tremendously while pursing my PhD at the Swiss Federal Institute of Technology (EPFL) and conducing research at MIT.”
Xiaowen Dong, MSc Signal Processing and Communications graduate
The course will appeal to graduates who wish to pursue a career in a range of industries such as communications, machine learning and data science, radar, medical imaging and wherever signal processing is applied. It is suitable for graduates who wish to develop the specialist knowledge and skills relevant to this industry and as advanced study in preparation for research work in an academic or industrial environment, or in a specialist consultancy organisation. All lecture courses are at the cutting edge of research in this field.
During the academic year students study compulsory taught courses, which include formal lectures, laboratory demonstrations, and practical exercises. Following the end of semester two, MSc students will complete a research project, which will normally be based upon a real-world problem posed by academic staff. The project is reported by a thesis. The taught courses in semester one start with fundamental theory followed by more advanced courses in semester two, and teaching of theory is supported by one MATLAB based course with experimental work. The project will build on the theory taught and the topic will usually be based on the current research at the Institute for Digital Communications (IDCOM).
Each course consists of a balance of lectures, seminars, and demos.
- Digital Communication Fundamentals
- Discrete-Time Signal Analysis
- Image Processing
- Probability, Estimation Theory and Random Signals (PETARS)
- Engineering Research Methods with Grand Challenge
- Advanced Wireless Communications
- Advanced Coding Techniques
- Machine Learning in Signal Processing
- Adaptive Signal Processing
- Array Processing and MIMO Systems
- Digital Signal Processing Laboratory
- Signal Processing and Communications: Project and Thesis
While studying the taught courses, students will also undertake prepatory work for their project. This dissertation, which will be based on a real world problem posed by academic staff, will be completed over the summer months. Many recent projects use modern machine learning, including deep networks, as a framework for problem solving and students in the MSc have access to a dedicated GPU rack to accelerate the training of their algorithms
Funding and Finance:
The School of Engineering and the University of Edinburgh offer many scholarships and bursaries. These range from course specific funding options, to general MSc scholarships. You can visit the University's scholarships website to find out more.
The School of Engineering also has several courses which are eligible for the Postgraduate Loans (SAAS) which is a loan system for Scottish/EU students. For more information and to find out about eligibility visit our Postgraduate Loans webpage. The Scholarship and Student Funding website also has an excellent search tool, to help you find funding available to you.
Fees and Living Expenses
Certain fees and other additional programme costs (eg research costs, class field trips) must be paid in full by each postgraduate student at the beginning of each academic session in September. More information about fees and additional costs can be found on the degree pages.
In terms of living expenses, you do not need to provide evidence of funding, however, you should be aware that, in applying for admission, you will be taking on a major commitment in terms of both time and money. The University recommends approximately £150 per week if living in University self-catered accommodation and £180 per week if in University catered halls (these figures include rent, lunches and personal expenditure). The University of Edinburgh's Fees and Finance section has more information available about fees and living expenses which you should take a moment to read over.
*Please note that courses are subject to availability and may change.
- Dr Javier Escudero Rodriguez, Programme Director
- Dr James Hopgood, Director of Discipline
- Dr Nicholas Polydorides, MSc Project Coordinator
- Professor John Thompson
- Dr Jiabin Jia
- Dr Majid Safari
- Dr Sotirios Tsaftaris
- Professor Bernard Mulgrew
- Dr David Laurenson
- Professor Michael E Davies
- Dr Mehrdad Yaghoobi
- Dr Wasiu O Popoola
- Professor Tharmalingam Ratnarajah
For graduates who wish to stay in Scotland, numerous national and international companies based in Scotland's "Silicon Glen" such as Keysight, Cirrus Logic, Dialog Semiconductors, Xilinx, IndigoVision, Leonardo, and others provide excellent employment opportunities.
IDCOM is one of the leading institutes in the UK in signal processing and digital communications. All academics are internationally recognised experts in their field and you have the opportunity to participate in cutting edge research in signal processing,digital communications, and machine learning. Students in the past published peer-reviewed research papers from their project work, which has helped them to secure PhD scholarships at top universities worldwide. In addition, each year we always strive to offer PhD scholarships to students who are at the top of the MSc class.