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(e.g. neural ODEs and SDEs), identifiability and interpretability, large language and sequence models, and multimodal data integration. This position will be based at the world-leading CRUK Cambridge
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and loss of migration across western Europe. Benefitting from the strong expertise of the supervisory team in stork ecology, movement analysis and spatial models, the project will leverage large
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Environment - Wiley Online Library Additive Manufacturing: A Comprehensive Review Big data, machine learning, and digital twin assisted additive manufacturing: A review - ScienceDirect Full article: Achieving
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wind farms in the UK and neighbouring countries is expected to triple in less than five years. Newer wind farms are also deploying very large turbines of 14 MW or more, meaning that wake effects between
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intensity of these changes. This PhD project will ultimately enable aircraft to reroute safely and efficiently in real time as weather evolves. By merging scientific machine learning, large-scale data
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river channels, altering their topography, destabilising banks, and changing how water and sediment move through large rivers. While these impacts are becoming clearer, what remains poorly understood is
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narrow down what parts of our genome are actually important for defining modern human-specific biology. This project will analyse data from these ultra-large datasets, alongside data from our great apes
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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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writing and implementing code alongside extracting information, trends, and patterns from large datasets. Topics to explore during this PhD project include: Investigating available software options Methods
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threats to biodiversity. Freshwaters are disproportionately affected by such invasions, and home to a disproportionately large proportion of biodiversity, especially invertebrates. They also provide