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Field
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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framework that compares and blends complementary paradigms of physics informed machine learning (such as PINNs, ODIL)—to (i) super-resolve experimental data, (ii) infer unknown parameters such as the
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multimodal satellite Earth Observation and machine learning can be used to quantify cyclone and storm damage in plantation forests. The core focus could be on integrating pre-storm LiDAR with post-storm
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well as retinal fundus images, we will explore analysis of new eye image datasets including OCTA and CCM images for diagnosis of diabetic neuropathy Machine Learning: We will develop artificial intelligence (AI
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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for computer, lab, and fieldwork costs necessary for you to conduct your research. There is also a conference budget of £2,000 and individual Training Budget of £1,000 for specialist training Project Aims and
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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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equipment (e.g., 3D scanning, surface inspection). Familiarity with data analysis tools (e.g., MATLAB, Python, or similar) and basic knowledge of machine learning is an advantage. Familiarity with research
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interest, narrowing the scope to natural or cultural sites, and integrating diverse remote sensing datasets. The supervisory team offers interdisciplinary expertise in geospatial analysis, machine learning
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of bacteria in the human gut, in-depth work with next-generation as well as 3rd generation sequencing technologies, then this PhD will be right for you. The ideal candidate will enjoy learning about metagenomic