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, structural dynamics and structural reliability theory, and you will work with data and cases from real infrastructure. You will be supervised by Professor Jochen Köhler (structural reliability and risk
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learning pipelines for multilayer segmentation and nanoscale transistor classification from microscopy images; (b) Designing graph-based inference models capable of reconstructing higher-level logical blocks
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) Developing deep learning pipelines for multilayer segmentation and nanoscale transistor classification from microscopy images; (b) Designing graph-based inference models capable of reconstructing higher-level
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especially SMEs. Duties You will take Ph.D. courses while performing thesis work in the form of, for example, literature, articles, design studies, construction and programming tasks, theory development
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project Can AI interpret graphs like a human materials scientist that relates diagrams to composition temperature, pressure, synthesis, processing and uncertainty? The PhD candidate will develop and
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of the defining challenges of the coming decade, and it is exactly where this PhD sits. At TU/e you will join the Information and Communication Theory Lab, a group with a long track record in classical coding and
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Creating superpositions of massive objects with a superconducting qubit: Can we test if gravity is quantum? Job description The radical theory of quantum mechanics is known to describe the fundamental
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process. This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying
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into applications. TRILOGY brings together 11 leading institutions across Europe to train 16 Doctoral Candidates at the forefront of theory and experiment in ultrafast science. The programme offers a unique
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investigate how the strengths of modern machine learning can be combined with the rigorous foundations of control systems theory to create a new generation of intelligent underwater robotic systems