40 web-programmer-developer-"https:" "https:" "https:" "https:" "https:" "https:" scholarships at Cranfield University
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to develop cutting-edge quantitative and applied environmental skills with real-world impact. It is a fully funded NERC CENTA PhD Studentship for 3.5 years with CASE support from BASF. Successful home-fees
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
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will handle real human waste samples to develop robust protocols for solid and liquid waste characterization, microbial profiling, and safety validation, including pathogen screening. Focus areas include
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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
to create solutions that are not only functionally excellent but also economically viable for large-scale deployment in diverse global contexts. This project aims to develop comprehensive design and
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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to identify the material degradation and coatings applications details in extreme environments. A novel techniques/method will be developed with focus on better prediction and more accurate measurement of
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sampled. This PhD study will address this research challenge. Cranfield is the largest academic centre for postgraduate studies in Science and Technology in the UK. Focused on developing applied research to
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to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre are among the world leaders in through-life approaches for high value
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This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and