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Field
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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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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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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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. 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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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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threats to biodiversity. Freshwaters are disproportionately affected by such invasions, and home to a disproportionately large proportion of biodiversity, especially invertebrates. They also provide
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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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-term risk to society (WEF, 2025). The increasing advance of large language models (LLMs) has led to a rapid rise in LLM misuse by malicious actors, for the purposes of low-cost generation of fake news
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. when do we stop modelling? How do we track / score the quality of the model What is the required level of quality over time How can quality be brought to the required level Can Machine Learning, Large
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undertaken in the NHS require a few days stay in hospital. However, it is possible to discharge some patients on the same day as their operation. We are preparing for a large randomised controlled trial by