Master of Science in Signals, Systems and Control
University of Malta
Full time, Part time
EUR 400 / per year *
Earliest start date
* Local/EU/EEA Applicants: Annual Enrolment Fee: Eur 400; Non-EU/Non-EEA Applicants: Total Tuition Fees: Eur 13,400
- Course title: Master of Science in Signals, Systems and Control
- Course code: PMSCSSCFTT7
- Postnominal: M.Sc.(Melit.)
- Level of qualification: Second Cycle
- National Qualifications Framework level: Level 7
- Duration: 3 Semesters
- Mode of attendance: Full-time
- Total ECTS credits: 90
- Coordinator: Simon G. Fabri
- Delivered by: Faculty of Engineering
This programme of study is also offered on a part-time basis. Please consult the Registrar's website for more information pertaining to courses offered by the University.
The MSc course in Signals, Systems and Control provides the necessary academic, practical and professional knowledge for students to learn and achieve high-tech competencies and advanced technological skills in the interlinked areas of signal processing, dynamic systems and automatic control systems. These three areas are the crucial building blocks of modern engineering methodologies applied for the design, development, implementation and analysis of complex systems, ranging from engineering applications and industrial problems to more mundane situations such as financial modelling and environmental control.
Throughout this course, one learns how to take a transdisciplinary approach to look out for, and capture, the similarities and structures of the dynamics of different systems and processes, how to extract useful information from typically large amounts of data generated by such systems, and how to optimise and control their behaviour. The course will cover the relevant theories, design methodologies and implementation techniques within the areas of system modelling, signal processing, dynamics and systems, automatic control, computer vision, machine learning and computational intelligence. On course completion, these skills and knowledge could be applied across a wide range of professional areas such as system automation, process control, biomedical engineering, manufacturing, transport and robotics, to name but a few.
This course provides students with the skills and knowledge to:
- apply a transdisciplinary systems theoretic approach to handle complexity and to formulate appropriate mathematical models for a wide range of dynamic systems, signals and information sets;
- analyse and extract information from signals, images and data sets using appropriate signal processing techniques;
- design algorithms for extraction of information and patterns from signals, images and data sets;
- analyse the performance, stability and robustness of closed-loop control systems;
- design and implement automatic control systems using a wide spectrum of control design techniques;
- seek relevant knowledge and information from reliable sources such as textbooks, monographs, journals and electronic information systems;
- comprehend, organise, analyse, integrate and connect together the various theories and methodologies delivered during the course;
- critically analyse, review and evaluate relevant information in an independent manner;
- creatively apply sound methodologies from engineering, mathematics and IT for the design, development and implementation of systems and algorithms for automatic control, signal processing, machine intelligence and automated systems.
- to plan and execute a research project, as well as presenting it to an audience and documenting it.
Course intended for
The course is targeted for graduates in engineering, information technology, physics, mathematics and related areas.
Career opportunities and access to further studies
Graduates will be able to apply the high-tech skills acquired during this course in a wide range of engineering, industrial, research and other professional disciplines that require the input of scientists and engineers who are specialised in the analysis, design and control of processes from a systems-based perspective. These include applications in automation, process control, biomedical engineering, manufacturing, transportation and robotics, to name but a few.