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Project Overview The University of Sheffield, funded by the EPSRC and in collaboration with Shell, is offering a fully funded 4-year PhD studentship through the EPSRC Industrial Doctorate Landscape
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. This PhD project focuses on a pivotal aspect of the fusion fuel cycle: efficient tritium extraction from lithium-based breeding media. In particular, Tokamak Energy’s innovative liquid lithium blanket design
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to improve structural durability, reduce material consumption, and support the UK’s net-zero goals. Funding notes: The position includes a full scholarship for UK-based PhD candidates and a half-scholarship
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Joint Industrial and EPSRC-funded PhD studentship in the Synthesis and Processing of Novel Biomaterials, in partnership with Haleon Applications are invited for a PhD Studentship, with an October
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research question of this PhD project is: How does extreme weather (e.g. heat waves and storms) affect the indoor environment (e.g. temperature, humidity, air quality), household behaviours and health, and
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
This is a fully-funded 4 year PhD offering an annual tax-free stipend of £20,780, tuition fees and an enhanced research and training grant. This PhD is one of a number of projects hosted by
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Project Overview This PhD project is part of an Innovate UK-funded research programme focused on developing a novel ammonia-fueled engine and generator set (genset) demonstrator for harbour and
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Programme Overview This PhD is part of the Engineering Hydrogen NetZero (EnerHy) Centre for Doctoral Training (CDT), a newly established EPSRC-funded initiative focused on advancing research and
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an original programme of research working with ecologists Dr Ashley Lyons and Dr Anne Oxbrough in collaboration with Dr Steven Ewing at the RSPB Centre for Conservation Science. This PhD is part of the Cumbria
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to air pollution in the future, and planning further policy changes. This PhD project will develop statistical modelling frameworks that are able to handle large-scale, complex, and correlated time series