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High speed photography to investigate surface wear and fatigue in railway rail and wheel steels
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environments and inaccurate prior maps, to name a few. In order to cope with these challenges different methods will be developed. Knowledge of Bayesian methods for sensor data fusion, mapping and multiple
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main project by addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods
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campaigns including programmed screening or Bayesian optimisation. You will characterise the resulting materials, in terms of their properties and performance for an intended application. Sustainability will
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, especially LIDAR, radar and others. Tracking is also part of this task since it require monitoring the areas of interest and autonomous decision making. Possible applications to this research are: Unmanned
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the ground, in different weather conditions. 4) develop methods for sensor management and data fusion linked with inference and decision making, jointly applied to several wildfire detection tasks. 5) embed
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High speed photography to investigate surface wear and fatigue in railway rail and wheel steels School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof D Fletcher
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. PAHs, heavy metals) will be used to infer pollution source. 3) What behaviour change solutions may reduce environmental pollution from solid fuel burning? Co-design/piloting of a behaviour change
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interview) Experience in ultrasound instrumentation (assessed at: application and interview) A strong track record of publishing research in established journals (assessed at: application) Good team working
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insights based on user interactions and project experiences. ● Maintaining and optimizing JIRA board workflows, ensuring efficient project tracking and task management. ● Working closely with