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within trusted digital environments. Their research focuses on ontology-driven conceptual modelling, FAIR data stewardship, and model-driven system/service engineering, dealing with data-driven services
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, and mineralogy Independent, self‑driven researcher with a strong problem‑solving mindset Proven team player, able to collaborate across multiple institutions Critical thinking to assess model
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are equipped with highly sought‑after skills in modelling, simulation, and data science, preparing them for impactful careers in research, technology, and beyond. If you’re excited by the idea of using advanced
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strategic priorities in Digital Twins, Environmental Intelligence, and Data-Driven Engineering, using advanced computational modelling to support ecosystem resilience and sustainable management. The project’s
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Join a fully funded, industry-sponsored PhD at the University of Nottingham (Mechanical & Aerospace Systems research group), in partnership with the Manufacturing Technology Centre (MTC). You will
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/Computer Engineering, Computer Science, Applied Maths or related. Strong skills in AI techniques/ML/optimisation (Python/Matlab); familiarity with probabilistic modelling, time-series or control/power
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with CamDragon Co. Ltd, a Cambridge-based SME offering engineering consultancy and STEM education
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Join a fully funded, industry-sponsored PhD at the University of Nottingham (Mechanical & Aerospace Systems research group), in partnership with the Manufacturing Technology Centre (MTC). You will
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language model (LLM)-based genome design tools with bioprocess engineering to create next-generation therapeutic conjugative plasmids. These engineered plasmids will be optimised for industrial-scale
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are fundamentally limited by a "one model for one task" design philosophy. This approach incurs prohibitive engineering costs and yields brittle solutions with poor generalisation to new network conditions, trapping