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Field
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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of distributed MIMO, and/or coordinated multi-AP operation (under study in the Wi-Fi 8 standardisation workgroup), using Hardware Description Language on FPGA, based on the open-source openwifi project (https
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architected materials or metamaterials (MTM) that can undergo targeted non-linear response. You will develop a computational framework that can reveal novel Multiphysics (thermo-mechanical) MTM solutions
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different VME types. Build predictive spatial models for VME distribution and resilience under future climate scenarios. Training The candidate will gain skills in: Deep-sea survey techniques using remotely
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, boosted by AI-data augmentation for extrapolating spectrum patterns from multiple sources. To design a scalable computing framework using a physics-informed neural network for distributed spectrum analysis
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) further study of the method, to understand how the 13C signal develops and is distributed in the plant, and how sampling can be optimized to show such effects of even shorter dry periods, typical
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of the temporal and spatial distribution of the exhaust gases in the atmospheric layers after the launch vehicle has passed through is therefore crucial for drawing conclusions about their climatic influence. Tasks
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD project investigates predator avoidance and the distributed brain circuits
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Are you excited about building cybersecurity platforms that are secure, explainable, and compliant by design? Do you want to combine real-time authorization, distributed ledgers, and verifiable
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Starting Date 1 Jun 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Reference Number 101227121/ DC9 Marie Curie Grant Agreement Number 101227121 Is the Job related