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within materials science and engineering. Use cases will be defined within different manufacturing techniques of lightweight structures to enable novel development of materials and process design. The PhD
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
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rules in networks of complex spiking neuron models in the application field of geolocalization: Building up simulation model for networks of complex neurons with topologies close to neuroscience models
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these new noise sources, influenced by complex building structures and in the presence of other noise sources, is limited, and scientific studies to understand the impact on people are therefore needed
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the German tradition (e.g., Kant, Humboldt, Goethe) 3. Its complex reception in Germany and beyond 4. Its contemporary relevance for environmental studies and scientific discourse Project activities include
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induced seismicity. Current models remain limited by the scarcity, heterogeneity, and noise of available data, as well as by incomplete knowledge of the subsurface. Physics-Informed Neural Networks (PINNs
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towards the next-generation co-design platform, accelerating the development cycle for complex interdisciplinary systems. Motivation Aircraft design is a highly complex process that must balance performance
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into useful chemical products is at the heart of the Net Zero transition. In liquid-phase heterogeneous systems, controlling which product forms and understanding why it forms remain one of the field's most
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ABHSSYS (Acoustic Black Holes for Silent SYStems, Grant agreement ID: 101227712) is a European Doctoral Network funded by the Marie Skłodowska-Curie Actions (MSCA), dedicated to advancing innovative
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the design of a scalable, interoperable, and resilient quantum internet architecture and protocol stack for real-world operation in hybrid quantum–classical networks across intra- and inter-domain settings