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Field
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are offering a one-year contract for a PhD position in complex systems and complex networks, with a particular focus on network geometry and its implications for the structure and function of complex systems
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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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capabilities in reasoning, planning, and generalisation, acquired through extensive pre-training, provide the foundation for a true cognitive engine capable of managing network complexity holistically
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
generation of wireless communication (6G) to extend network coverage, supporting diverse data-intensive applications such as immersive extended reality and autonomous systems. However, aerial 6G networks will
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Almost all radar systems currently transmit from the same location. A drastic departure from this sensing architecture is distributed radar – enacted by a coherent network of spatially distributed
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frequency regulation, energy scheduling, and overall smart grid system optimization. Moreover, such complex interconnections between power system dynamics, communication networks, and information
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their applications. Using machine learning and related tools to enhance quantum memory advantages in stochastic simulation. Using advanced tensor network techniques to enhance the modelling of complex, memoryful open
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and recent evolutionary genetic discoveries, utilizing large-scale bioinformatic databases and resources. Background: The human brain is a highly complex network of interconnected regions—the connectome
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, and processing conditions influence their behaviour, creating a vast and complex landscape that traditional experimentation cannot navigate efficiently. This project addresses this challenge by bringing
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complexity seen in patients. This Marie Skłodowska-Curie Actions (MSCA) doctoral network PhD project takes a fundamentally new approach: embedding animal models in a translational framework that connects