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element models. ● Work collaboratively with other colleagues for the validation of the finite element models of rib samples based on in situ mechanical testing data. ● Lead the model uncertainty
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Rethinking scholarly and editorial practices for born-digital data Digital Humanities Institute PhD Research Project Self Funded Dr Isabella Magni Application Deadline: Applications accepted all
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. We take a macroecological approach to addressing this challenge, mining large databases of marine biodiversity data to understand the ecological, evolutionary, and environmental factors that drive
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(work-related expenses are covered, you do not require access to your own vehicle) Provide information, advice, and guidance to prospective students acting as a positive role model. Work closely with
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limited to machine learning, Natural Language Processing, large language models, data visualisations, and linked open data, can help streamline and improve editorial workflows. At the same time, it
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, and spray-on electronics, working with several industrial collaborators, including Tata Steel, Rolls-Royce and the National Nuclear Laboratory. The candidate will benefit from working within a large
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low carbon district heating as a key strategy to enable large scale decarbonisation building sector, to achieve net zero by 2050. Currently, 2- 3% of heat demand in the UK is covered by district heating
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development in modern cements formulated with SCMs is therefore urgently required, to enable quality control and make them practical for use in large-scale construction. This PhD uses advanced spectroscopic
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. Cyber-physical power systems deploy the latest information and communications technologies to enable the data and information flows across different entitles of physical networks. Such ‘cyber’ systems
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landslides to replicate real-world scenarios. Model forests will be designed to mimic tree uprooting and breaking under landslide impacts, providing valuable data to validate and refine the numerical models