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Field
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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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the properties of composite, biological networks which consist of stiff filaments and liquid inclusions which arise from liquid-liquid phase separation. We will use a multi-scale approach bridging scales from
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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meshing of complex shapes, the project will substantially shorten preparation times and accelerate the adoption of high-order methods in industrial design and analysis. As the PhD researcher on this project
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, where current workflows still depend on substantial manual model clean-up. By removing the reliance on de-featuring and enabling reliable high-order meshing of complex shapes, the project will
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Department: Mathematics Title: Multiscale modelling of polymer network constitutive behaviour Application deadline: All year round Research theme: Applied Mathematics How to apply: Click the 'Apply
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, reliability, and availability of complex industrial systems while making maintenance strategies more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance
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). "Statistical field theory applied to complex networks” "Quantum geometrogenesis – Graph theoretic approaches to building spacetime” web page For further details or to discuss alternative project arrangements
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embedded in the Doctoral Programme in Complex Systems Science at the University of Luxembourg. The modelling approaches developed in this project share conceptual similarities with adaptive network and
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network congestion. However, these PEDs substantially increase the complexity of protection of LV networks, with major issues of voltage/current waveform distortion and reduced fault level necessitating