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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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the right tools including AWS and our on premise infrastructure Work on designing resilient and reliable services used by large numbers of users Use a wide-range of technologies to develop and host websites
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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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. 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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will also be an integral member of the large, multidisciplinary BuildZero project team, and will contribute to wider project tasks, events, and outputs. Further information can be found at https
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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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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
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into the microgrid. The system needs to be optimised to deliver the lowest cost / kWh of delivered energy to the load, preferably comparable to that of a grid connection. The project runs alongside a large UKRI funded
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further information about the group’s work and publications at http://osbornelab.group.shef.ac.uk. Enquiries should be directed to Colin Osborne c.p.osborne@sheffield.ac.uk. Please apply for this project