School of Electrical Engineering and Computer Science invites applications for one doctoral student position in the area of dependable autonomous systems focusing on integrating machine learning with system modelling and verification.
The aim of the project is to develop a framework for modelling and verification of autonomous systems often called learning-enabled systems, i.e., the systems that rely on machine learning components to perform their functions. Such systems should be able to work in a safe and reliable way even in the presence of the environmental uncertainty or hostile operating conditions. There are two complementary research challenges that should be addressed at the development and operation time. The first question is how to improve training by automatically discovering scenarios of environmental uncertainty and augmenting the training data sets. The second question is how to design efficient dependability monitors that recognize the hazardous situations and ensure safety at run-time.
The doctoral student should be able to work on both – the theoretical foundations of the framework and its application. The expected application domain is automotive.
Third-cycle subject: Computer science
Supervision: The doctoral student will be supervised by Elena Troubitsyna.
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