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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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will develop a flexible neuroprosthesis for the motor cortex capable of supporting the production of complex movements. This project is part of a multidisciplinary collaborative effort with the labs
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the different types of systems and develop a core graph data system that can serve as a common building block. This way, redundancies in keeping multiple cop-ies of graph data in different systems could be