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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
-latency, and scalable operation in aerial 6G networks. In this regard, Large Language Models (LLMs) have recently emerged as a key technology to achieve adaptive 6G spectrum management. The core idea of LLM
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such goals via large-scale experiments or via simulation modelling? Then we have 2 PhD positions available, within the Dutch-Danish project Robotic Intercropping , within the focus areas ‘Agro-ecological
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discovering research and potentially pursuing a PhD. Expected skills • Solid background in numerical methods (PDEs, finite elements, scientific computing). • Interest in modeling, model order reduction, and
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validation in representative environments. The successful candidate will gain expertise in electrochemical sensing, microengineering, and computational modelling, and will join an interdisciplinary research
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of pseudorange correction models. Enforcing such constraints offers substantial potential benefits, including faster convergence, improved generalisation, and reduced overfitting. At the same time, these benefits
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8 Nov 2025 Job Information Organisation/Company CNRS Department Laboratoire d'analyse et d'architecture des systèmes Research Field Computer science Mathematics » Algorithms Researcher Profile First
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pilots to real-world systems. The overarching aim is to deliver a scalable approach, pairing shared “aggregator” models with household-specific “client” models that exchange knowledge while keeping data
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project aims to develop state-of-the-art computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the
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We are looking for 4 highly motivated PhD students to join our research team for a project focused on battery modelling, state estimation, fault diagnosis and control. Information Batteries
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basic models and patient-derived specimen with cutting-edge technologies. One of our recent projects has been to better understand human polyneuropathies by using single nuclei and spatial