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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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extraction, as well as the model feature and machine learning based TCM into the framework of digital twins. This allows building up and updating a digital twin of machine tool dynamics via a completely data
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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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applications, for example Word, Excel and Google networked office applications. Experience of using computer based financial systems, for example SAP. Excellent Customer service skills, with experience
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, appointment details, and other essential information into computer systems. Process payments efficiently and securely. Answer incoming calls, take messages, and transfer calls to the correct departments
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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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for workshops, liaising with wider team and professional services staff to place orders as necessary. Drive the project van to and from events where required. Ensure all equipment, resources, and machines
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from level 3 through to level 7. In this role, you will be required to develop teaching resources using a variety of active learning strategies, to ensure the apprentices have a high-quality learning