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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
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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
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for appointment at Grade 7 with a salary range of £39,424- £47,779 per annum with amended duties and responsibilities. About us The MMM Unit is based at the Big Data Institute and John Radcliffe Hospital. We work
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simulation workload and update the solver data structures when the mesh changes. These approaches would be applied on modern large-scale heterogeneous parallel computing environments where both CPUs and GPUs
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will use a high-fidelity large eddy simulation (LES) code and scientific machine learning tools, such as real-time optimisers, in order to simulate wind farms exposed to various atmospheric inflows. Some