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analytics tools have been massively developed in the research community to address this challenge. These AI-based analytics tools are data-driven and black-box, so the interpretation of how predictions
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be transferable skills in the technical area of optimisation, industrial exposure, or soft skills including presentation skills, project management, and communication skills. There are also numerous
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development. The student will also have access to Cranfield’s state-of-the-art laboratories and a vibrant research community, as well as chances to present their work at international conferences and build a
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-solving, teamwork, and communication—setting the stage for a thriving career in research and innovation. This project is situated within the evolving field of cyber-physical systems (eCPS), which has
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modelling software. Practical experience in advanced manufacturing techniques for novel materials. Opportunities to present research at international conferences and build a professional network across
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at international conferences and build a professional network across academia and industry. Development of expertise in cutting-edge experimental techniques, computational modelling, and interdisciplinary
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language proficiency (IELTS overall minimum score of 6.5). Also, the candidate is expected to: Have excellent analytical, reporting and communication skills Be self-motivated, independent and team player Be genuine
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science, mechanical engineering (or related field), manufacturing, chemistry or physics background. The candidate should be self-motivated, have good communication skills for regular interaction with other