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, detection, localisation, etc.) Reconfigurable/programmable radio environments and system/network-level antenna design Theory with guarantees (convex/non-convex optimisation, performance analysis, machine
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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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climate change-resilient infrastructure slopes. This PhD is co-funded and co-supervised by Network Rail. The aim of this project is to enhance the utility of InSAR (Interferometric Synthetic Aperture Radar
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mental status examinations and neuroimaging scans, which are often inaccurate. There is an urgent need for cost-effective and accurate diagnostic tools for early detection of neurodegenerative diseases
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to arrange the tuition fees and living expenses. Find out more about fees here . Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study
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similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical
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Early and accurate cancer detection remains a critical global healthcare challenge, with profound implications for patient outcomes and treatment strategies. While Time-of-Flight Positron Emission
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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early