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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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nutrition and exercise trials Excellent oral and written communication skills Ability to critically appraise scientific methodology and data Ability to work well individually and as a member of a larger
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Funding information: The studentship is for 3.5 years and provides a tax-free stipend of £20,780 per annum for the duration of the studentship plus university tuition fees. Due to funding restrictions
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
: £37,174 - £45,413 Fixed-term: The funds for this post are available for 24 months in the first instance. To apply online for this vacancy and to view further information about the role, please click 'Apply
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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the coupled effect on supersonic combustion. This data can then help support future design efforts, which requires validation data where the effects of thermal warpage can be included. To achieve
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qualitative data acquired through focus groups and interviews with regulators, manufacturers and engineers, and deriving analytic insights into material perceptions and values. In addition, they will oversee
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, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data, disambiguate historical agents, and contribute
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resources efficiently, and clearly convey complex information. Previous experience with decarbonization in the transport sector, LCA, EE-MRIO models, sampling design, and emerging cities including working