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are challenging to inspect using conventional non-destructive inspection techniques. As a result, larger safety margins are often required in structural design, leading to heavier structures, while maintenance
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learning paradigms. The framework will support rapid prototyping, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms
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staff position within a Research Infrastructure? No Offer Description Challenge: Design building renovations under future uncertainty. Change: Develop uncertainty-aware life-cycle methods to optimise
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, you will analyze resource flows, evaluate circularity scenarios, and support sustainable design and decision-making across interconnected sectors. This PhD is part of the Greenhouse in Transition
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of wireless technology and excited to embark in the exciting new world of photonics, we invite you to apply for this PhD opportunity! Information This project aims to innovate detector design to overcome
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other inside a tissue. In this project, you will build interpretable-by-design machine learning models for biological data that offer biological insights in a direct way. Such models will be applicable
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the project "Circularity as Opportunity: Engineering Hydrogen-Resistant Circular Steels (CIRHY)", a 6-year research and innovation programme developing next-generation circular steels that can safely operate in
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imaging methods that are more robust and computationally efficient, while also providing a natural framework for uncertainty quantification and experimental design. A central question is whether suitable
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assemblies are challenging to inspect using conventional non-destructive inspection techniques. As a result, larger safety margins are often required in structural design, leading to heavier structures, while
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controllers for complex systems that are safe and verifiable by design. Information Neural networks can provide the flexibility needed to control increasingly complex dynamical systems, but their opaque and