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ERC project AToM (Adaptive Tokenization and Memory in Foundation Models) with a focus on designing, implementing, and publicly releasing LLMs with efficient architectures (including adaptive memory
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research proposal and their CV. The research proposal should fit well with one of the Centre’s main research themes, programmes and projects. More information about the Centre’s research programmes and
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research