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Field
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to direct drive and medium-speed permanent magnet generators, paving the way for more cost-effective and reliable offshore wind energy systems. *The information provided in this section will be
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to coordinate participant recruitment, OPM-MEG and eye-tracking data collection, analysis, documentation and reporting to meet deadlines. You will adapt existing and develop new scientific techniques and child
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the BioGeomorphology Laboratory flume, field datasets from restored and natural saltmarshes across the UK, and expertise from researchers in coastal ecology, hydrodynamic modelling, AI, and data science. Objectives
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and laser-scan data. These models underpin decisions impacting net-zero ambitions, yet interpretation remains slow and subjective. We need tools that make geological reasoning faster, more transparent
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learning (FL), where multiple UAVs collaboratively train artificial intelligence models without sharing raw mission data. This supports privacy and efficiency, but it also creates a serious security risk: a
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and visual monitoring during deployment, working in coordination with the RT3D development led by E-Sailor 15. The research includes conducting laboratory and in-orbit experiments using data from
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, Materials Science, or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject and the ability to think analytically and creatively. Good computer
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‑dependent data is often unavailable and many traditional monitoring methods are too resource‑intensive or unsuited to the complex, delicate habitats used by juvenile fishes. This project aims to offer both
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generate biologically interpretable models of zoonotic emergence and ultimately aid in developing new tools for human pathogen surveillance. This project offers training in bioinformatics, data science and
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reservoir heterogeneity. This project will integrate core observations, wireline logs and seismic data to develop geological and petrophysical models that constrain reactive reservoir simulations