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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
present at top AI/ML venues and validate ideas on real platforms. Mentorship focused on visionary brainstorming, in-depth technical discussions, and collaborative work culture on both theory and systems
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easier to detect and measured experimentally. However, it is not well known yet how this process emerges and how one can control it. This PhD project will focus on developing the necessary theoretical
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theories and models. This project aims to develop new insights into how bedrock incision processes interact with geological and climatic factors (i.e. spatially variable uplift, shield building, mega
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Supervisors Primary Supervisor - Dr Calum Williams Secondary Supervisors - Dr. Maciej Dabrowski , Prof Simon Horsley This PhD studentship will develop 3D-printed optical metamaterials to control
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- skills – experience: analytical skills, ability to demonstrate good knowledge in system modelling – simulation, (classical or modern) control theories or control applications with evidence Desirable
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trade-offs between efficiency, cost, and emission control. To fully realise ammonia’s potential as a clean energy carrier, a fundamental rethinking of the combustion process is needed. This PhD project
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and mathematical tools in quantum physics, quantum information theory, and related fields. It is a strong asset if you have already acquired expertise and demonstrated your ability to perform rigorous
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aforementioned tasks with the following actions: Develop the principles and theories for governing the scalability principles for building innovative robotics end-effectors that can access geometrically complex
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analytical frameworks grounded in Mean Field Game (MFG) theory and Multi-Agent Reinforcement Learning (MARL), which are tailored for eCPS. These frameworks will facilitate the creation of effective control