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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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system configurations, experimental setups and operational data. The scientific ambition is to develop methods that combine physical models and data-driven approaches for adaptive, real-time operation of
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. The main activities include: Designing machine learning models that can detect unusual, unsafe, or attacked operating conditions. Developing data-driven models that capture how faults and attacks spread
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machine learning models that can detect unusual, unsafe, or attacked operating conditions. Developing data-driven models that capture how faults and attacks spread through a system, and using them to make
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strategic initiative to further strengthen the department’s expertise in digital and AI-driven research methods. Your work tasks • Develop and carry out an independent research project under supervision