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the objectives and development of the research programme on the Oncogenic and Immunogenic Roles of Transposable Elements in Cancer. The appointed PDRA will be integrated into a multidisciplinary team and will
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machine learning under real life constraints of clinical integration/validation and healthcare regulatory translation/commercialisation. The position is part of the project `Integrated autofluorescence
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the opportunity to deliver tangible impact by integrating academic innovation with industrial challenges. This is an exciting opportunity for a researcher with expertise in power systems, optimisation, or AI
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, passionate about applying advanced technologies to sustainable manufacturing. About the Role You will play a key role in research, development, and integration within the Circular Robot 5.0 consortium
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are applying an integrated approach that combines understanding of pathogen biology and plant immunity to inform the development of climate-resilient crops, using the interaction of bacterial pathogens with
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integrating multi-modal perception and tactile feedback, for locomotion and manipulation. You will be responsible for the design, development, implementation and evaluation of learning-based loco-manipulation
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against cancer. Within the School, the Comprehensive Cancer Centre (CCC) integrates molecular discovery, drug-development pipelines and patient-facing trials, with strengths in personalised medicine, immuno
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of the project will be to develop trajectories of dietary change towards healthier and more sustainable diets with a particular attention to alternative protein sources, and to integrate environmental, health, and
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of the project will be to develop trajectories of dietary change towards healthier and more sustainable diets with a particular attention to alternative protein sources, and to integrate environmental, health, and
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detection framework for tipping points. Contribute to the design of scalable and interpretable forecasting strategies for large climate simulators, integrating adaptive sampling and Bayesian techniques