57 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" PhD scholarships in United Kingdom
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, machine-learning tools, and Lagrangian transport modelling. You will be based at the British Antarctic Survey and work closely with experts at the University of Leeds and Exeter, who provide cutting-edge
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to also improve and scale the process. We have made major contributions in this area, including the use of Machine learning to discover new cryoprotectants [Nature Communications 2024, 15, 8082
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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composites To propagate uncertainty in material behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help
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research agenda. The student will join the State of Wildfires Project (https://stateofwildfires.com/ ) at UEA, receiving advanced training in satellite data analysis, machine learning, and climate and fire
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, the UK Parliament, and various media outlets including the BBC, and its members have earned numerous international awards. Learn more at https://pinholab.cc.ic.ac.uk . Your goal: Develop advanced numerical
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, machine learning, or (astro-)physics (in particular cosmology, galaxy formation, or general relativity) will be an advantage. What we offer: Inspiring working atmosphere: You will have the opportunity
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is appropriately multi-disciplinary, at the interface between AI, environmental science, meteorology and epidemiology. Corresponding skills (machine learning, environmental and public health data
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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avenues may include linking plankton size patterns to krill dynamics, carbon export or nutritional quality, or developing tools for rapid ecosystem monitoring using machine-learning approaches