Do you want to conduct top-notch research and bridge the gap between theory and application regarding software analysis? As a PhD Candidate, you will focus on developing faster and more scalable techniques for the formal analysis of safety-critical systems. Join a diverse environment where you can focus on how research contributes to solving real-world problems and willingness to learn is valued.
Your main responsibilities as a PhD candidate will be to conduct cutting-edge research. We expect that this research leads to the development of faster and more scalable techniques for the formal analysis of safety-critical systems that operate based on limited information about their environment.
In particular, we aim to develop novel algorithms for the analysis of (extensions of) Markov Decision Processes and Partially Observable Markov Decision Processes, motivated by a series of applications in the dependability and security domains. The project allows to freely explore connections between runtime verification, model checking, automata learning, planning and reinforcement learning, depending of the joint interests of you and the principal investigator.
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