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'. Please quote the advertised reference number, 'SSEHS/SMN25', in your application. To avoid delays in processing your application, please ensure that you submit the minimum supporting documents .
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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costs. Condition monitoring (CM) of rolling element bearings, hereafter called bearings, has been the main point of attention for many decades in the industry for maintenance. This is because bearings
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and corrosion in aqueous CO2-containing environments (such as geothermal systems) is the continuous injection of chemical inhibitors into the process fluid. These inhibitors can function through a
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holder will be required to have practical experience in high-density microelectrode pattern on soft substrates with good understanding of advanced microfabrication processes, electrode substrate
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process It is anticipated that the selection process will take place on 8th July. This will consist of an interview, test and tour. We plan to let candidates know if they have progressed to the selection
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
, further exploring the carbon-related impact of polymer breakdown. The project will also incorporate artificial intelligence (AI) and machine learning to optimise degradation processes and data analysis
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”, at Brunel University London, who must start by 1st October 2025. BCAST is a speciality research centre in metallurgy with a focus on processing of metallic materials for light weighting applications
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exhaustive, and the PhD candidate will be required to undertake such tasks and responsibilities as may reasonably be expected of a PhD candidate. Application process The application should include: a
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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