36 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"M.V" PhD positions at Cranfield University
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, environmental science, urban sustainability, geospatial analysis, or quantitative modelling. We particularly welcome applicants who are excited about integrating ecological understanding with data-driven methods
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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function of urban blue spaces influence perceptions. It will subsequently explore and evaluate the types of information and knowledge required to improve the understanding and appreciation of urban blue
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, intelligent monitoring systems and predictive technologies have become essential competitive advantages. This project sits at the intersection of data science, engineering, and design innovation, addressing
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/position/type of hardware. Cranfield overview and Sponsor Information/Background: We have a long history in space systems, having undertaken space studies since the 1960s. Our current research has
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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operating filters. Quantify operational performance including headloss recovery, filtrate turbidity, biological stability and lifecycle carbon—using high-resolution sensor data and life-cycle assessment tools
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directly addresses one of the most pressing challenges in modern information security: the malicious use of synthetic media. The relevance is acute, as deepfakes and AI-powered phishing campaigns are being
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits