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-Adapted Transformer Model incorporating Hybrid Linguistic-Contextual and Anomaly-based features. To evaluate the model against traditional and general deep learning models using comprehensive de facto
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wrinkles can occur, which cause parts to be scrapped. To minimise material and energy wastage, digital models of the manufacturing processes can be developed and linked to process control and optimisation
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materials is still evolving, especially for temperature- and rate-sensitive systems like prepreg. This project aims to address these challenges by developing a suite of deployable tools and predictive models
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Finance MSc Mathematical and Theoretical Physics MSc Mathematical Modelling and Scientific Computing MSc Mathematical Sciences MSc Mathematics MSc by Research Mathematics and Foundations of Computer Science
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, where detailed information on the fund will be available in December 2025. The opening date for applications is 1st January 2026, and the closing date is 15th April 2026. We advise that you check the COSF