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PhD Scholarship Develop GNSS-IR methods and integrate GNSS-derived observations with satellite data and land surface models through data assimilation to deliver accurate, high-resolution soil
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, data science, or related - Strong programming skills (Python and/or R) - Experience with machine learning or data analysis - Knowledge of deep learning frameworks Application Procedure Interested
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testing and assessment of device-assisted aerosol delivery under clinically relevant operating conditions. Data processing, image analysis, uncertainty assessment and experimental interpretation using
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own thinking, analysis and motivation. Applicants are responsible for verifying accuracy of all information, including references. Shortlisted applicants will be expected to discuss their statement
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, computer vision, federated learning, foundation models, adaptation techniques, multimodal learning, longitudinal image analysis or related areas, evidenced through coursework, research projects
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: · Systematic review and meta-analysis · Evidence synthesis and critical appraisal · GRADE guideline development methodology · Living evidence methods · Clinical epidemiology
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observations of sub-Neptune exoplanets, with a focus on the most promising water world candidates. Develop analysis techniques to disentangle planetary signals from instrumental artefacts and stellar noise
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social media and online platforms. The project will use natural language processing (NLP), large language models (LLMs), and network analysis to identify coordinated harassment, anti-gender equality
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AI infrastructure. The Opportunity This is an unprecedented opportunity for an outstanding data science and AI PhD candidate interested in brain data analysis and AI, supervised by Dr Mahsa Salehi
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with