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Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science Research theme: "Materials Characterisation" "Data Science and Machine Learning in
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variability to address specific research questions. Student profile: Essential skills: The student is expected to have a background in one or more of the following areas: environmental science/ mathematics
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degree or equivalent in a related discipline. This project would suit individuals with academic or industrial experience in electronics, electrical engineering, systems engineering, or AI/data analytics
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. The outcomes of this research will support cross-disciplinary applications such as environmental monitoring, chemical analysis, and systems biology, providing innovative solutions that enhance the integration
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manufacturing methods and environmental storage conditions on the material properties and performance over time. The aim of this project is to understand how the properties of polyolefins (such as polyethylene
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and Britain are world leaders and major exporters. This high technology global industry is worth more than £30 billion per annum. Current challenges are arising from the need to address environmental
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information about the CDT, please visit the website or send an email to hello@fusion-engineering-cdt.ac.uk . The candidate should have a 1st / 2.1 class Undergraduate or Masters degree (or equivalent) in
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partner universities. For further information about the CDT, please visit the website or send an email to hello@fusion-engineering-cdt.ac.uk . The candidate should have a 1st / 2.1 class Undergraduate or
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of the candidate Essential Academic background in biology, geography, or environmental science. Ability to carry out field work in river systems, including sampling for macroinvertebrates, water quality, river
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Sciences, Environmental Sciences, Earth Sciences, Material Sciences, Biochemistry. Must have analytical chemistry skills and good numeracy; experience of mathematical coding would be desirable. Start date 1