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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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their own research programme as well as support in the delivery of AI upskilling and expertise transfer to government. What you would be doing The objectives for the role are: to deliver ground-breaking
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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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tackling foraging tasks, to work out which algorithm best explains how foragers decide to leave. You will have some experience in computational modelling of behaviour, such as decision-making models
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the US National Science Foundation. The overall aim of this project is to determine the geometry and plumbing of the hydrothermal system of an active submarine arc volcano and its relationship with
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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end
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to work on meaningful projects with direct clinical relevance. About the role In this role, you will develop and implement computer vision and deep learning algorithms to analyse CT and MRI data from
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-fostering prototypes through co-design with children, creating evaluation frameworks to assess children's algorithmic agency in educational contexts, and establishing design principles that prioritize
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Faculty/Directorate Faculty of Engineering, Computing & the Environment School/Function Faculty General (ECE) Contract type Fixed Term Contract Location of vacancy Penrhyn Road The Role Kingston
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researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious research aims to develop new AI for shared human-AI decision-making in