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Field
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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data, you will develop an AI-driven optimisation framework to identify where such interventions can deliver the greatest combined benefits for people and the environment. The research combines urban
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, despite its widespread application, polygraph data capture and analysis has received limited systematic research and does not yet incorporate modern sensors, computing and analytical techniques. Project
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We are recruiting a PhD student to integrate data-driven methods with NMR spectroscopy to enhance the characterisation of cell culture media and metabolites, increasing throughput and reducing
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to the space-based LISA observatory. The research will advance post-Newtonian waveform modelling through improved analytical techniques, incorporate strong-field information from numerical relativity simulations
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breeding. The project will involve extensive industry consultation therefore the ideal candidate will be possess strong communication, relationship-building, and analytical skills and be confident working in
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existing biomedical foundation models (e.g., Med-PaLM) using techniques like Low-Rank Adaptation (LoRA). Big Data Analytics: Managing and analysing complex, multi-modal data from globally significant
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profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
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the research. They will conduct relevant systematic and/or meta-analytic reviews to describe the current literature and inform their research. They will undertake qualitative data collection and analysis and use
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marine sciences, biological oceanography, ecology, or computer sciences. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a