Embedded Systems Engineering

  • MSc
  • Part-time
  • English
  • 4 Semester
  • Graz
  • 20 Places
Application period
from 02.10.2023

Embedded Systems Engineering - Study track of the Master degree programme in Electronics and Computer Engineering*

Our excellent training for the electronics and electrical engineering industry offers plenty of practical experience, state-of-the-art equipment, and close cooperation with industry. You will learn everything you need to know about embedded software and hardware development, system architectures, system-on-chip, data analysis and machine learning for a successful future career. As a future engineer, you will design intelligent software and reliable hardware in order to integrate artificial intelligence into chips, vehicles, factories, and many other innovative products.

Key subject areas

Innovative. Agile software and hardware development.

The high level of complexity of intelligent electronics requires new approaches to product development. You will learn about the latest methods and principles of agile software and hardware development, allowing you to develop products in a flexible and iterative manner. You will design quality assured, reliable software and hardware for a dynamic world.

AI. Machine learning and data analysis.

You will deepen your understanding of statistical methods and data analysis in order to develop data-driven solutions for a variety of applications. You will learn to understand and apply advanced machine learning techniques and algorithms to extract patterns and insights from large datasets.

High-tech. System-on-chip design.

Today’s integrated circuits combine a multiplicity of functions on a single chip, making them a “system on a chip”. You will gain a thorough grounding in microelectronics and microprocessor technology, so that you can design and validate complex and powerful chips.

High-performance. Real-time computing.

Real-time responses to inputs and events are critical for applications such as autonomous driving, industrial automation and energy networks. You will study modern computer and software architectures for embedded systems, enabling you to use machine learning and signal processing algorithms to process large volumes of data with minimal delay.

* Subject to Approval by the Relevant Bodies

Entry requirements

Applicants must have a degree in a STEM (science, technology, engineering, mathematics) subject with 180 ECTS credits. They must provide evidence of at least 30 ECTS credits in electronics and computer science.


Application mode:
Online Apllication

Application time:

Admission procedure:
Application and Interview

Start of studies:

Study information days:
OPEN HOUSE: https://www.fh-joanneum.at/en/university/events/open-house/

Tuition fee:
no tuition fees for students from the EU, EEA and Switzerland

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