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testing research, this project will develop techniques to automatically discover scenarios in which the robots may fail – in advance of their deployment – ultimately making them more efficient and safer
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grade. Generate data through comprehensive laboratory grinding tests on various rail grades to train and validate the ML model. Utilise numerical modelling to establish acceptable thresholds for surface
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at higher risk offered PSA blood tests which are not definitive. Our research aims to develop an image-based approach to screening, combining PSA testing with MRI to better identify aggressive cancers
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markers. Develop machine learning models capable of predicting Category 1 emergencies based on real-time audio features extracted from calls. Work iteratively with YAS researchers to test and refine