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). Despite its innovative nature, the project is grounded in complementary expertise and strong collaboration between the partners, ensuring feasibility and successful integration of hydrogels with organ
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machine learning techniques to derive clinically meaningful clusters based on CV risk factors and digital biomarkers; Identify phenotypic extremes to guide downstream immunological analyses; Collaborate
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used to develop networks capable of self-learning and self-optimisation, adapting to real-time changes in traffic and demand. The successful candidate will contribute to designing solutions that optimise
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friction models. Integrating Experimental Data: Collaborate with experimental teams to incorporate data from calcium imaging, confocal microscopy, and high-resolution video recordings. Use experimental data