Assistant Professor In Formal Methods and Neuro-Symbolic AI

Assistant Professor position in the Department of Mathematics and Computer Science at TU/e, focusing on Formal Methods and AI for Zero-touch Systems. The role involves designing and developing Neuro-Symbolic methods for verification, enabling development of models for zero-touch autonomous systems, and contributing to scientific roadmaps in Neuro-Symbolic AI. The position is part of the Formal System Analysis (FSA) Cluster and addresses the interdisciplinary area of Formal Methods and AI to improve reliability of autonomous and self-adapting systems. Responsibilities include conducting mission-driven research on autonomous, self-healing systems with societal impact, teaching, mentoring students and staff, and building a research community. The successful candidate will work on developing theory and techniques combining Formal Methods with symbolic and sub-symbolic AI approaches, including Runtime Verification, Shielding, Reinforcement Learning reasoning, Neural Network Verification, and eXplainable AI.