650 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" positions at University of Sheffield
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accepted all year round Details The advent of easily accessible high performance computers or computer clusters and numerical techniques such as finite element methods (FEM) facilitates the highly accurate
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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can
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might lead to the development of novel anti-cancer therapies. Preliminary data indicate that the degradation of ECM by cathepsin proteases is required for ECM internalisation. The overall aim
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their own funding. For fee status information, see https://sheffield.ac.uk/new-students/tuition-fees/fees-lookup#M An enhanced fee of £4000/annum will be applied to these fees to cover research expenses
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protein machinery regulating vesicle docking, priming and fusion will be investigated. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying References
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to produce similar ‘carbon-capture’ plants using gene-editing technology. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes Open to Self
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for the project prior to submitting your application. [1] https://www.weforum.org/impact/carbon-footprint-manufacturing-industry/ [2] https://www.gov.uk/government/news/government-publishes-uks-third-climate-change
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(IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language. Please
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developing mathematical modelling and observational data analysis using high spatial, temporal and spectral resolution state-of-the-art solar telescopes (e.g. SST and/or the 4m aperture DKIST). There is also
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to capture the variability of end-of-life composite materials. These algorithms will be combined with destructive and non-destructive test data, and then be used to develop predictive capabilities for grading