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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
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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. This project will develop responsive manufacturing technology that will have sufficient flexibility to overcome such problems by utilizing intelligent machine learning to control the printing process in real
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Knowledge of machine learning or multi-omics data integration would be highly desirable Essential Application/Interview Deep interest in musculoskeletal research and translational science Essential
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Knowledge of machine learning or multi-omics data integration would be highly desirable Essential Application/Interview Deep interest in musculoskeletal research and translational science Essential
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at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will involve designing innovative QML approaches and collaborating
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are looking for an ambitious candidate with a strong background in mathematical and statistical methods for both physics-based modelling and machine learning, and their application to engineering problems in
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machining, welding and cladding and non-destructive testing. As a Project Manager, you will be working within groups in the AMRC or across multiple groups. In this exciting opportunity this role will be based
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will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
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preferences for them using birds as a model system. Capitalising on recent advances in computational neuroscience and machine learning, specific objectives are to (1) quantify common design features of avian