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. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration with the Department
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
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developing neurotechnologies for treating brain disorders? In this PhD you will work with datasets of neuronal activity in animals and humans. You will apply computational approaches to describe spatial and
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advance the development of the Tool’s algorithms and functionality. As a key innovative component of D-Suite, this open-source tool will achieve wide industry visibility, and will be formally evaluated by
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
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algorithmic learning.) The Department of Computer Science and Technology is an academic department that encompasses computer science along with many aspects of engineering, technology and mathematics. We have a
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in the study of problems in quantum many-body physics through the lens of quantum information and quantum computing? Do you enjoy studying complex quantum mechanical systems both from a physical and a