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architectures. This includes among other: (a) design and implementation of machine learning and GenAI models, (b) efficient training and inference on GPU-based systems, (c) fine-tuning and optimization of large
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unsustainable land management in the EU's land-use sector. It aims to reduce biogenic emissions and enhance ecosystem resilience by utilizing Living Earths, integrating FAO LCCS with optimized Earth Observation
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, computational intelligence and machine learning, autonomous systems, optimization and networks, embedded and real-time systems hardware and software, fault diagnosis, cyber-security, reliability, resiliency and
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modelling, designing, optimizing, and experimentally validating new system architectures, as well as contributing to collaborative research activities, preparing project deliverables, assisting with
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prototype database of polymorphous materials. Contribute to the development of a Fortran-based HPC code. Implement routines for temperature-dependent optical and transport properties. Optimize workflows
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on their fields and optimize decision making approach for pesticides application. Additionally, MANIFESTO project provides environmental sustainability derived from reduced pesticides application. Last, MANIFESTO
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Optimization models) applications and other tools or services as part of ERATOSTHENES responsibilities in Pharos-CY; Contribute to the preparation and submission of Pharos-CY deliverables and other technical