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propagation models that incorporate the effects of fire effluents, validated through controlled experimentation. You will develop tomographic inversion methods and anomaly-detection algorithms capable
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for Quantum-enhanced, distributed radar signal processing techniques that maximise target Signal-to-Noise Ratio (SNR). The algorithms we will derive will be applied and tested in the context of target detection
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programme you are applying for. To Apply for this project please click on the following link - https://www.exeter.ac.uk/study/funding/award/?id=5733
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-cases of classical supercomputers, the development of quantum CFD algorithms will be of widespread benefit upon the arrival of fault-tolerant quantum computing. This project involves the adaptation
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, Computer Science or a closely related field, ideally with a strong focus on quantum computing and numerical simulations. Experience in data-reuploading quantum algorithms, optical quantum computing and quantum
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with CamDragon Co. Ltd, a Cambridge-based SME offering engineering consultancy and STEM education
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elaboration of biocatalysis for synthesis. A doctoral position is available for 3-years to work with Professor Florian Hollfelder at the Biochemistry Department of Cambridge University (https
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to maximise early outbreak detection. Active intervention: developing decision-making algorithms that recommend effective public-health interventions. Reinforcement learning (RL) provides a natural framework
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statement that shows evidence of engagement with this advert. Further information on the PhD in Computer Science programme can be found at: https://www.cst.cam.ac.uk/admissions/phd All applications should be