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, which options become visible, and how agency is distributed between humans and algorithmic systems. In this PhD project, you will study AI-supported decision-making from a representational perspective
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manufacturing machines and advanced mechatronic systems, rely on ultra-reliable, low-latency, and deterministic communication between distributed sensors, controllers, and actuators. Ensuring such performance
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unpredictable, standard foundation models often output overconfident, flawed embeddings when faced with unprecedented climate anomalies. To solve this, you will also develop rigorous Out-of-Distribution (OOD
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scenario; Develop a novel self-calibrating, heterogeneous distributed platform capable of providing the necessary sensing, transport, compute and data aggregation capabilities on demand. Consider how partial
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algorithms to guarantee the reliable operation of semiconductor machines, together with a highly innovative industrial partner in the Brainport region. If all these sounds fascinating, then this PhD position
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of