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University of Cambridge About us Contact us Job Opportunities Jobs Applying for a job My applications Right to work What we can offer Living in Cambridge Temporary work Work experience Volunteering Page not found This page cannot be displayed. If you are returning to a previously accessed job...
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Overview This PhD project will take a comprehensive approach to exploring how corporate sustainability disclosure practices evolve in response to the integration of Machine Learning (ML) within
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at the intersection of machine learning, bioinformatics, and computational pathology. Project Overview: Integrating histopathological imaging with omics (e.g., transcriptomics, genomics, proteomics) holds tremendous
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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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Early-stage failure prediction in fusion materials using machine learning CDT in Developing National Capabilities for Materials 4.0 PhD Research Project Directly Funded UK Students Prof Christopher
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Applications are invited for a University Assistant Professorship in the broad area of Machine Learning. The successful candidate will join the Computational and Biological Learning Lab (CBL
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Machine Learning Methods for Enhancing Autonomy of Unmanned Aerial Vehicles in Wildfire Detection and Localisation School of Electrical and Electronic Engineering PhD Research Project Self Funded
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adaptability of wearable and medical devices, and safer human-machine interaction. Machine Learning (ML) is an emerging technology with significant potential in integrating and embodying soft robotics
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for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four
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Machine Learning Methods for Autonomous Robot Navigation, Localisation and Pipe Inspection School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova