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Field
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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bone cells toward regeneration. These will be characterised using AFM and rheology, followed by immune–osteogenic co-culture studies to evaluate mechanotransductive signalling. The resulting data will
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Skills Background in biochemical or chemical engineering, biotechnology, or microbial processes. Hands-on experience in fermentation, microbial cultivation, and analytical techniques (HPLC/GC). Familiarity
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, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the
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. This is further hindered by a lack of diverse big data resources and matched, powerful analytical tools. As a result, progress in the field has been characteristically slow over the last 50 years
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-culture studies to evaluate mechanotransductive signalling. The resulting data will inform mathematical models linking material mechanics to biological responses, enabling the sustainable design of next
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. Hands-on experience in fermentation, microbial cultivation, and analytical techniques (HPLC/GC). Familiarity with bioprocess modelling and simulation tools (e.g., Aspen Plus, MATLAB, or Python), TEA, and
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-gradient-driven diffusiophoretic focusing for power-free analyte concentration Integrate nanomaterials and microfluidic components into scalable, user-friendly LFA prototypes Validate device performance
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culture, biomaterials, or biological assay techniques. Good analytical and problem-solving skills and the ability to work both independently and in a multidisciplinary team. Excellent written and verbal