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Field
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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enhance system reliability and safety, aligning with the UK’s NetZero targets. Aim You will have the opportunity to build a high-fidelity process simulation and perform experimental validation to assess
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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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. Aim You will have the opportunity to build a high-fidelity process simulation and perform experimental validation to assess the structural performance of composite sleeves under operational conditions
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Hydrogen is the most abundant molecule in the universe, and its interaction with surfaces plays a key role in a huge range of processes, from star formation to the safe storage of rocket fuel
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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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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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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 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