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approach is to apply foundational techniques grounded in logic, semantics, and verification. This work takes place within the CYCLIC project: Cyclic Structures in Programs and Proofs, a collaboration among
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component-level specifications to system-level specifications. This PhD position will focus on the use of contracts for verification, i.e., aimed at guaranteeing system-level properties on the basis
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for verification, i.e., aimed at guaranteeing system-level properties on the basis of component properties. The position is part of the recent large project “Contracts for Control System Design”, funded by
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position will focus on the use of contracts for verification, i.e., aimed at guaranteeing system-level properties on the basis of component properties. The position is part of the recent large project
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, computational fluid mechanics, high-performance computing, and physics-informed machine learning. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty
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dealing with the scalability challenge, we work on two main research objectives. First, we aim to understand how to learn models that are useful for upstream planning, scheduling, and verification tasks