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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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17 May 2024 Job Information Organisation/Company Cranfield University Department HR & Development Group Research Field Other Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2
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operation with local communities, which is a pioneering effort in this field. You will be joining a large, international consortium with over 30 academic and industrial members. We will look into many aspects
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as an academic member of the MK:U Education team with a specialism in a field related to Data or Digital (for example, analytics, visualisation, maths and programming, Big Data). This element of
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to travel to field sites overseas. You will have experience of working with farmers and other rural stakeholders, ideally using participatory methods and collection of field data (e.g. environmental
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autonomously to analyse, interpret, and evaluate scientific data and present the results of laboratory work and problem solving clearly and concisely in written and oral form. The apprenticeship provider is
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facilities to ensure timely testing of energetics • Run analyses and tests using specified and agreed techniques and models • Acquire and interpret research data and results
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utilised with the aim of efficiently analysing large datasets, the extraction of meaningful information and the creation of a chemical database. The PhD student will be involved in the adaptation of the CRIM
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economy and de-centralised manufacturing. To enhance process efficiency (clean) by researching sensors and big data for factory management, product service systems, factory modelling and artificial