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develop roots preferentially upslope to provide anchorage against horizontal soil sliding. Greater understanding of how root system architecture and geometry provide resistance to different combinations
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
-latency, and scalable operation in aerial 6G networks. In this regard, Large Language Models (LLMs) have recently emerged as a key technology to achieve adaptive 6G spectrum management. The core idea of LLM
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design and transformation, ontology engineering and knowledge representation, construction management and digital construction, sustainability in the built environment and climate change, and project
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1. Project overview Electrochemical sensing plays a central role in next-generation health technologies, enabling real-time monitoring of physiological environments with high sensitivity and low
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outlining how you would approach the project, and an up-to-date CV. Under programme name, please select 'Architecture, Building and Civil Engineering'. Please quote reference RAINDROP-CH. Only applicants with
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, the construction of the geological model remains a significant challenge. The geological model is key because it constrains the volumes and data used when inferring the mineral resources, which in turn inform
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science, engineering, mathematics, or related subject) Proficiency in English (both oral and written) Essential to have strong foundations in computer systems through degree courses or equivalent work experience
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PhD studentship in Trustworthy Multimodal AI under Lightweight and Data-Efficient Architectures Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26
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private. This PhD will focus on three strands of work: 1) Innovate NILM model structures. Design efficient neural network architectures for both aggregator and client models that meet strict accuracy
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monitoring, and autonomous systems. However, most advances rely on large datasets and computationally intensive architectures that are impractical for scenarios constrained by limited data and resources