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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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general, can you decide interesting properties of your input by examining only a tiny part of it? In this era of big data and information explosion, reading the entire input is prohibitively costly
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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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, 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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-down 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
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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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and GTC/HiPERCAM and NTT/ULTRACAM high-speed photometric data for a large number of magnetic white dwarf binaries. You will be responsible for developing new methods for analysing these objects, with
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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