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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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, however, these may not always be able to provide the spatial and/or temporal coverage that is required. In such cases, information from ground measurements can be combined with information from other
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the understanding of offshore turbulence in spatially varying flows. The focus will be on open channel flow dynamics and controlled experimental studies will be designed and conducted to generate and characterise
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-service involvement, develop typologies of need, and uncover spatial and temporal trends. Combining data science techniques with stakeholder engagement, the project aims to generate actionable insights
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. Experimental studies will be performed in wind tunnels with advanced measurement techniques with high spatial and temporal resolutions. Realistic car models (DrivAer models) will be considered in this study and
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of the infrastructure, design and execution of large‑scale measurement campaigns, and development of data‑driven models for room acoustics and spatial‑audio. The specific research direction will be finalised after
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or merit level from an internationally recognised university, in spatial planning, urban geography or a related subject, and an equally strong undergraduate degree in related subject areas. Applicants should