Learn to design embedded systems for any application: from tiny parts in devices such as digital watches to MRI and machines in the high-tech industry.
In essence, the Master’s in Embedded Systems is about specialising in software and hardware engineering. You learn to design a system architecture including the software and hardware components. This means you will develop and test not only the software that runs on the embedded system but also the hardware. Moreover, you will investigate if the integrated software and hardware meet the intended use, functionality, and performance. As you will learn by doing, you will use logic analysers, oscilloscopes, factor network analysers, spectrum analysers, soldering irons, computer boards, sensors, and actuators at our labs to design efficient embedded systems.
By the end of the Master’s, you will be able to design an embedded system for any application and domain: for instance, an embedded software that maximises the energy efficiency of a power grid. Or think of radar systems on ships that need to meet strict requirements concerning reliability and power consumption. While you can focus on a broad range of topics, we advise you to choose a theme by following a set of elective courses. We recommend you to choose the theme at the beginning of your Master’s. However, you are free to take elective courses that don’t comprise a specific theme.
The five themes are:
- Computer Architecture: get a deep understanding of how computer systems are designed and organised and how you can optimise their performance, power consumption, and reliability.
- Embedded AI: understand the challenges and opportunities of implementing AI in embedded systems, namely power constraints and real-time processing requirements.
- Internet of Things: learn about different types of sensors embedded in IoT systems and how they connect and exchange data.
- Dependable Computing: is your embedded system responding in a reliable way? How do you prove the embedded system does what it should do?
- Cyber-Physical Systems: model robust embedded systems by integrating physical components, such as sensors and control systems, with computational ones, such as processors and memory.
As a graduate of this Master’s, you have specific scientific knowledge, skills, and values that will help you in your future career.
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