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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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. English language requirements: Applicants must meet the minimum English language requirements. Further details are available on the International website . Funding information: The studentship is for 3-years and
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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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, 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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the PhD has been awarded. Fixed-term: The funds for this post are available for 18 months in the first instance. To apply online for this vacancy and to view further information about the role, please
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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all employees are eligible to live and work in the UK. Further information Apply online
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to apply For further information please contact: Name: Dr Francesco Fanicchia Email: Francesco.fanicchia@cranfield.ac.uk If you are eligible to apply for this studentship, please complete
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letter (maximum 2 pages) and your CV (maximum 2 pages). Please make sure that your cover letter and CV provide adequate information on your academic ability, research potential, communication and