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Field
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. The goal is to contribute broadly to research on applications of AI in medicine, and in particular to the development and validation of novel computational language models, algorithms, and tools
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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interaction and analytics using AI. Key Responsibilities: Development of artificial intelligence (AI) technologies to perform human-robot interaction and analytics System integration of the developed algorithms
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and developing/improving the algorithm for estimating radiative fluxes and heating rates. The candidate will also conduct observational analysis to diagnose physical processes of cloud, precipitation
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. N., Benn, C., Kitto, K., Knight, S., & Zhang, V. (2024). A technical democracy design experiment: Making the UK exam algorithm controversy game. Design Studies, 91, 101245. Hicks, B., Kitto, K., Payne
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital
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blind and low-vision individuals in navigating both outdoor and indoor urban spaces. The project's initial phase will employ machine learning models, computer vision algorithms, and real-time sensory
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time