MASTER’S / BACHERLOR’S THESIS – DISTRIBUTED REAL-TIME SYSTEM AND SOFTWARE DEVELOPMENT (M/F/D)

fortiss is the research institute of the Free State of Bavaria for software-intensive systems and services with headquarters in Munich. The institute currently employs around 150 employees, who collaborate on research, development and transfer projects with universities and technology companies in Bavaria, Germany and Europe. Research is focused on state of the art methods, techniques and tools of software development, systems & service engineering and their application to reliable, secure cyber-physical systems, such as the Internet of Things (IoT). fortiss has the legal structure of a non-profit limited liability company (GmbH). Its shareholders are the Free State of Bavaria (as majority shareholder) and the Fraunhofer Society for the Promotion of Applied Research.

To further strengthen our Architectures and Services for Critical Infrastructures team, we are looking for new team members:
Master’s or Bachelor’s Thesis Student in Distributed Real-Time Systems and Software Development (m/f/d)
 
Increasing complexity of modern cyber-physical and real-time embedded systems introduces challenges regarding the efficiency and robustness of these systems. The coexistence of highly critical tasks and less critical ones in systems with limited resources and strict real-time constraints requires the investigation of dynamic, adaptable and responsive approaches to achieve both resource optimization and safety in the system.

With this in mind, at the fortiss Architectures and Services for Critical Infrastructures field of competence, we research and develop analysis and methods to create software architectures and techniques for dynamic distributed real-time systems. These systems must be scalable, stable, robust and be capable of handling workloads in a cost and energy-efficient manner, while ensuring safety. The techniques applied in this research span from the design and implementation of a mixed-criticality embedded operating system to the application of machine-learning methods for an optimal execution of the tasks.

We are looking for motivated master’s or bachelor’s students in search for a thesis. The specific topic for the thesis is open to discussion with the candidate, with a focus in the afore mentioned system characteristics.