The Master’s degree in Computer Engineering provides knowledge and skills in the core areas of Computer Engineering, including computer science, cybersecurity, robotics and control, machine learning, electronics, telecommunications, and the Internet of Things.

This Master’s programme equips students with the methodological foundations and technological capabilities required to design, develop and deploy a wide range of systems and applications demanded by today’s information society, in order to organise, manage, process, retrieve and transmit data and information, with due regard to cybersecurity.

The programme offers students the opportunity to complement their academic preparation by undertaking industrial placements as well as research dissertations. This is made possible by an extensive network of collaborations with local, national and international companies, as well as with universities across Europe and worldwide. The programme is delivered entirely in English.

Educational objectives

Knowledge and Understanding

Informatics

Upon completion of the Degree Programme, students will be able to identify, comprehend and report the principal results related to the following topics:

A1 – Operation of computer systems in adversarial environments.
A2 – Cost, functional and non-functional requirements for problems in the computing domain.
A3 – Methods for the automatic synthesis of procedures and algorithms from large datasets.
A4 – Methods, terminology and common notation for supervised and unsupervised machine learning.
A5 – Metrics and procedures for evaluating supervised and unsupervised machine-learning systems.
A6 – Formulation of discrete and continuous models for constrained and global optimisation.
A7 – Main network architectures and the operation of the different layers that make up the Internet protocol stack.
A8 – Communication protocols and architectures suited to Internet scenarios and Internet of Things devices, in terms of scalability, geographical scope and security.
A8 – Modern Web protocols and the design choices that motivated them.
A9 – Techniques and concepts for the design and implementation of information systems for large organisations.
A10 – Techniques and concepts for the collaborative development of complex industrial software systems.
A11 – Testing-oriented techniques for software design and development.
A12 – Techniques and concepts for web application development.
A13 – Usability and interoperability requirements in web applications.
A14 – Techniques and concepts for automated information retrieval from large volumes of unstructured data.
A15 – Techniques for the effective communication and visualisation of knowledge extracted from large datasets.
A16 – Core conceptual tools of cryptography.
A17 – Main protocols for communication using symmetric-key and public-key cryptography.

These outcomes are achieved through lectures, classroom exercises and independent study.

Achievement of the intended learning outcomes is verified through any mid-term assessments conducted during the learning activities and written and/or oral examinations at their conclusion.
 

Theoretical, Methodological and Technological Aspects of Networks and the Internet of Things

Upon completion of the Degree Programme, students following the Networks and the Internet of Things curriculum will be able to identify, comprehend and report the principal results related to:

A1 – Information theory, digital modulation, and error-control codes.
A2 – Communication systems, resources and requirements for efficient and secure use: bandwidth, power/energy, quality of service.
A3 – Architectures of modern wireless systems and related standards (cellular systems: GSM, UMTS, LTE; WLAN: IEEE 802.11; WPAN: IEEE 802.15; sensor networks; Internet of Things).
A4 – Characterisation and modelling of the wireless communication channel.
A5 – Enabling technologies for the wireless channel: diversity/multiplexing, OFDM, CDMA, MIMO, V-BLAST.
A6 – Characterisation of electronic systems used in the wireless field.
A7 – Design and implementation of communication systems using programmable devices (FPGA, DSP, USRP).
A8 – Characterisation of high-frequency devices and systems in both microwave and optical domains.
A9 – Characterisation and design of antennas and antenna systems.
A10 – Processing and transport of multimedia information over heterogeneous networks.

These outcomes are achieved through lectures, classroom and laboratory exercises, and independent study.

Achievement of the intended learning outcomes is verified through any mid-term assessments conducted during the learning activities and written and/or oral examinations at their conclusion.
 

Theoretical, Methodological and Technological Aspects of Electronic Systems

Upon completion of the Degree Programme, students will be able to identify, comprehend and report the principal results related to:

A1 – Devices and circuits for analogue electronics.
A2 – Architectures for digital electronics.
A3 – Programmable digital electronics.
A4 – Electronics for wireless networks.
A5 – Electronic processing of signals and images.
A6 – Power electronic systems.

These outcomes are achieved through lectures, classroom and laboratory exercises, and independent study.

Achievement of the intended learning outcomes is verified through any mid-term assessments conducted during the learning activities, written and/or oral examinations at their conclusion, and discussion of agreed in-depth thematic studies.
 

Theoretical, Methodological and Technological Aspects of Robotics and Artificial Intelligence

Upon completion of the Degree Programme, students will be able to identify, comprehend and report the principal results related to:

A1 – Continuous and discrete mathematical optimisation.
A2 – The theory of dynamical systems, with particular regard to the notion of a system, its mathematical representations and structural properties, together with the notions of state, equilibrium, stability and feedback.
A3 – Analysis and synthesis of control systems, and the theory of optimal and robust control.
A4 – The principal machine-learning techniques, evolutionary optimisation, and evaluation methodologies for systems based on these techniques.
A5 – Principles of operation of robots and their mechanical components.
A6 – Characteristics of agent-based systems and techniques for reinforcement learning.
A7 – Concepts relating to image formation and computer-vision techniques for keypoint detection, object detection and tracking.
A8 – Principles of Internet operation, technical aspects of cyber-attacks, and defensive mechanisms.

These outcomes are achieved through lectures, classroom and laboratory exercises, and independent study.

Achievement of the intended learning outcomes is verified through any mid-term assessments conducted during the learning activities and written and/or oral examinations at their conclusion.

 

Ability to Apply Knowledge and Understanding

Informatics

Upon completion of the Degree Programme, students will be able to:

B1 – Assess the principal cyber-attacks feasible in a given application and architectural scenario and the corresponding mitigation mechanisms.
B2 – Assess the principal risks associated with cyber vulnerabilities in a given application and architectural scenario and the corresponding prevention and mitigation mechanisms.
B3 – Evaluate and implement the most appropriate techniques for authentication and authorisation in web applications.
B4 – Determine when a problem is solvable using machine-learning techniques and provide an abstract formulation.
B5 – Design, implement and experimentally evaluate machine-learning-based application solutions in terms of effectiveness, efficiency, interpretability and applicability.
B6 – Design and implement exact, approximate and (meta-)heuristic algorithms to solve constrained and global optimisation problems.
B7 – Determine the communication architecture suitable for the requirements of a distributed application scenario in terms of performance, scalability and security.
B8 – Design a telecommunication network at a high level, mastering the concepts of routing, local networks, VLANs and VPNs.
B9 – Understand the operation of an existing network and use common tools for traffic inspection and analysis.
B10 – Design and build software prototypes using sector-standard tools, languages and libraries, including for machine learning, web programming and information retrieval (IR).
B11 – Determine the necessary software components at system and architectural level according to the requirements of the specific application domain, including for machine learning, web programming and IR.
B12 – Adopt software development techniques appropriate for industrial applications.
B13 – Adopt testing and refactoring techniques.
B14 – Evaluate and adopt leading practices in web interface design and the corresponding principles of usability and accessibility.
B15 – Evaluate the principal front-end and back-end development techniques most suited to a specific application domain, including strategic frameworks and programming languages.
B16 – Determine automated methods for extracting information from large volumes of unstructured data appropriate to the requirements of the specific domain.
B17 – Build tools for the interactive analysis and visualisation of knowledge extracted from large datasets.
B18 – Assess the principal web-application-specific cyber-attacks and the corresponding mitigation mechanisms.
B19 – Assess the principal communication-protocol-level cyber-attacks feasible in specific application domains and the corresponding mitigation mechanisms.
B20 – Design a communication session using symmetric-key and public-key cryptography.

These outcomes are achieved through lectures, classroom exercises and independent study.
 

Theoretical, Methodological and Technological Aspects of Networks and the Internet of Things

Upon completion of the Degree Programme, students will be able to:

B1 – Compute the capacity of digital communication systems and design efficient, including adaptive, modulation and coding techniques.
B2 – Characterise communication channels, with particular reference to wireless channels.
B3 – Use and develop simulation techniques for the design and optimisation of a communication network.
B4 – Know the principal techniques and current international standards for wireless communications, and be able to play innovative roles in this domain.
B5 – Design the principal electronic components required in a wireless system.
B6 – Design and implement prototype communication systems using programmable devices (FPGA, DSP, USRP).
B7 – Design high-frequency transmission systems in both optical and microwave fields.
B8 – Perform measurements on microwave and optical systems.
B9 – Compute antenna-system parameters and design the most suitable antennas for a given application.
B10 – Design and validate techniques for processing and transporting multimedia information over heterogeneous networks.

These outcomes are achieved through lectures, classroom and laboratory exercises, and independent study.
 

Theoretical, Methodological and Technological Aspects of Electronic Systems

Upon completion of the Degree Programme, students will be able to:

B1 – Design analogue and digital electronic networks.
B2 – Programme FPGA devices at different levels of abstraction.
B3 – Design linear digital filters, defining appropriate implementation architectures.
B4 – Design pipelines for the acquisition, processing and visualisation of images for specific applications.
B5 – Design and implement techniques for image processing and analysis.
B6 – Size and control static power-electronic converters.

These outcomes are achieved through lectures, classroom and laboratory exercises, and independent study.
 

Theoretical, Methodological and Technological Aspects of Robotics and Artificial Intelligence

Upon completion of the Degree Programme, students will be able to:

B1 – Formulate mathematical models, and design and implement quantitative methods and software tools to solve complex decision-making problems, identifying optimal (or sub-optimal) solutions.
B2 – Recognise the characteristics of a dynamical system in phenomena across various domains such as electrical engineering, computing, electronics, mechanics, chemistry and biology.
B3 – Analyse dynamical systems to investigate their behaviour, using both analytical and numerical tools.
B4 – Design state-feedback or output-feedback control systems and optimal control systems.
B5 – Apply the main paradigms of robustness analysis to systems characterised by model uncertainty.
B6 – Determine when a problem is solvable using machine-learning techniques, provide an abstract formulation, and design, implement and experimentally evaluate the machine-learning-based solution.
B7 – Carry out the kinematic analysis of a robot.
B8 – Identify a system amenable to modelling as a dynamical system and select the most appropriate reinforcement-learning techniques.
B9 – Recognise a computer-vision problem and characterise it; identify the most appropriate techniques to solve it and design and implement a solution based on them.
B10 – Analyse computer networks, assess their weaknesses in terms of cybersecurity, and design and implement the corresponding countermeasures.

These outcomes are achieved through lectures, classroom exercises and independent study.

Career Prospects

Employment and professional opportunities for graduates

Software Systems Specialist

This professional profile is highly relevant across a wide range of settings: small, medium and large enterprises; public and private research and development centres; IT and technology services within the public administration; and IT consultancy firms. It is particularly important in organisations engaged in software design and development, specialised systems and services for information systems, cybersecurity, and data analytics.
 

Data Analysis Systems Specialist

This profile is in demand in diverse contexts: small, medium and large enterprises; public and private research and development centres; IT and business consultancy firms; and IT and technology services within the public administration. It is especially pertinent to organisations that must manage large volumes of data collected by electronic and digital means.
 

Autonomous Systems Engineer

Opportunities arise in companies operating in Industrial Robotics, Automotive, Agri-Tech, Healthcare, Transport and Logistics, Aerospace, Renewable Energy, and Research & Development, in organisations of all sizes. Software development companies also represent a key employment destination.
 

Computer systems designers for fixed and mobile networks

This profile is relevant to small, medium and large enterprises; public and private research and development centres; providers managing fixed and mobile network infrastructures; and IT and business consultancies focused on network services. It is especially critical in organisations that need to design, develop, test and manage IoT and fixed/mobile communication systems.
 

Hardware and Firmware System Designers

This professional role is needed in small, medium and large enterprises; public and private research and development centres; and consultancy firms. It is particularly relevant to organisations operating in computing and consumer electronics, communications electronics, the production of IoT and embedded systems, high-tech industrial sectors, industrial automation and robotics, automotive, aerospace, and power/energy conversion.

 

Competences Associated with Each Role

Software Systems Specialist

Knowledge and skills gained in the core of the degree programme and through advanced study focusing on the methodological and technological aspects of software application development. Specific expertise in programming languages, systems engineering and cybersecurity.
 

Data Analysis Systems Specialist

Knowledge and skills gained in the core of the degree programme and through advanced study focusing on the methodological and technological aspects of software application development. Specific expertise in programming languages, and in methods and tools for machine learning and artificial intelligence.
 

Autonomous Systems Engineer

This professional applies knowledge acquired during the programme to the modelling and control of complex systems, optimisation, robotics, computer vision, and the use of artificial intelligence and machine learning, alongside solid skills in programming, cybersecurity and network communications. This integration enables the provision of methodological and technological solutions essential for the development of autonomous and intelligent systems.
 

Computer systems designers for fixed and mobile networks

Knowledge and skills gained in the core of the degree programme and through advanced study focusing on the theoretical, methodological and technological aspects of fixed and mobile communication networks. Specific expertise in computer networks, wireless networks and the Internet of Things, methods and tools for machine learning, and signal and image processing.
 

Hardware and Firmware System Designers

Knowledge and skills gained in the core of the degree programme and through advanced study focusing on the methodological and technological aspects of hardware and firmware systems. Specific expertise in signal and image processing, electronic systems design, design and programming of embedded systems, and methods and tools for machine learning.

 

Role in the Workplace

Software Systems Specialist

This professional deals with the design and development of applications and services based on software technologies. S/he interprets the requirements of the application domain from a functional, technological, organisational, security and regulatory point of view. Contributes to the definition of specifications for the various design and implementation phases. Participates in security analyses to identify risks and privacy mechanisms and processes. It deals with the design, coding, testing and maintenance of the architectural, software and system components of the product or service to be implemented.
 

Data Analysis Systems Specialist

This professional deals with the design and development of systems that operate on large amounts of data for machine learning, knowledge extraction, and optimisation of specific business and organisational functions. They determine the methods of data collection, use and analysis based on the requirements of the application domain and regulatory constraints. Contributes to the definition of specifications for the various design and implementation phases. Contributes to security analyses to identify risks and identify data protection mechanisms and procedures. Determines the most appropriate algorithms, analysis methods and validation of results for the context. Participates in the design, coding, testing and maintenance of the necessary software components.
 

Autonomous Systems Engineer

This profession is suitable for a wide range of contexts, from the management of industrial drones to autonomous driving of vehicles and collaborative robots in work environments. Experts in this field carefully analyse problem specifications, create a 'digital twin' of the system for simulation and validation, and design control algorithms based on mathematical models and artificial intelligence. These control algorithms aim to maximise performance while ensuring the robust safety of autonomous systems and the people involved in their operation. During development, informed technology choices are made with a focus on effectiveness, efficiency and cost. The management of communication with sensors and actuators also focuses on the security of the information transmitted, with particular attention to potential threats and vulnerabilities. Finally, the software produced is designed and implemented in accordance with the necessary ISO standards.
 

Computer systems designers for fixed and mobile networks

These professionals create, design, optimise, modify, develop and test computer systems, infrastructures and networks used for the acquisition, processing and transport of information and its use in multimedia applications and public and private remote monitoring and communication services.
 

Hardware and Firmware System Designers

These professionals design, optimise, modify, develop and test the hardware and firmware structures that underpin modern electronic systems (PCs, tablets, smartphones, IoT systems, medical devices, control units for cars, aircraft, drones, robots and measurement devices).

Final examination and degree

Characteristics of the final examination

The final examination consists of preparing a written dissertation that demonstrates the competences expected by the learning outcomes of the Degree Programme.

The dissertation must be developed independently by the student under the guidance of a supervisor agreed with the Programme Board, on a current topic of theoretical, practical or experimental interest in industry or scientific research. In particular, the dissertation proposed for the final examination shall always relate to a substantive experience that may involve:

• an original project;
• an in-depth study of a topic in basic or applied research;
• experimental research carried out in university laboratories or at external organisations.

The final examination concludes with the presentation and defence of the dissertation before an Examination Board constituted in accordance with the University’s Academic Regulations.

Part of the final examination may be undertaken within an internship or placement.