39 machine-learning-phd-particle-physics PhD positions at Cranfield University in United Kingdom
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. As industries increasingly rely on machines and automation to improve efficiency and reduce costs, ensuring the reliable operation of components like electric actuators becomes vital. This is
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This PhD project will investigate the recent field of study of Causal Machine Learning, which aims to modify and augment Machine Learning by using Causal Analysis techniques as a way to solve its
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, access, technologies, perceptions and discourses converge in time and space to impact the health and quality of freshwaters. In this project, the PhD student will adopt a critical perspective on the cause
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to monitor online the manufacturing process and development of damage in the material and the incorporation of heating and cooling. The Composites and Advanced Materials Centre at Cranfield has recently
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environment to streamline and optimise production processes. Manufacturing automation systems attempt to achieve enhanced human-machine interactions with a view to improving efficiency, productivity and the
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for this position has a BSc and MSc in environmental sciences, physical geography or biology, knowledge of metagenomic analyses, and a passion for the natural environment. This fully funded studentship is part of
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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An exciting PhD studentship opportunity fully-funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership (DTP). This project would suit students with a
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The ever-increasing use of data in real-world applications is a clear indication that we are moving into the era of Industry 5.0 where human-machine collaboration would be key to enable digital
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and process optimisation. This PhD, funded by EPSRC and a major UK Water Utility (Northumbrian Water), is seeking to implement advanced nanobubble technologies as a sustainable and efficient water