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patients with lung / cardiac MRI and improve patient experience. Image computing support for pulmonary MRI applications. Development of hardware for neonatal / paediatric MR applications Contribute to and
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local environment, but current imaging and transcriptomic resources are largely descriptive snapshots. This project will deliver a computational framework that integrates lineage-resolved, snapshot time
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and low power (yet high performance) RF circuits and hardware, spanning the entire field and spectrum of RF design. The purpose of this research project is to investigate present state-of-the-art
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Zero-Knowledge for Quantum Proofs: Quantum Computation and Cryptographic Primitives (S3.5-COM-Abdolmaleki)
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Bugging Out: When AI loses the Plot – Detecting and Taming Hallucinations in LLM-Generated Code (S3.5-COM-Wang)
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Explainable and Causal AI for Visual Analytics in Regenerative and Climate-Smart Agriculture (C3.5-COM-Cruz Villa-Uriol)
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-supervised by experts from Computer Science, Mechanical Engineering, and Sheffield Teaching Hospitals, ensuring a strong link between clinical application and technical innovation. CDT programme This
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information with a high degree of accuracy and attention to detail and will have previously supported student or programme related processes. They will also be able to build effective relationships with staff
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research project ‘Perceptual bias and the evolution of organismal communication signals’ as a Research Associate. The project willmake use of recent advances in computational neuroscience, machine learning
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for engines exhibiting varied degradation phenomena. Data-driven approaches, powered by machine learning, can offer superior performance but raise challenges of robustness and interpretability. Recent