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accepted all year round Details This PhD project focuses on using topological data analysis (TDA) in machine learning (ML) to study (exotic) quantum matter systems defined on a lattice. TDA is a technique
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Metalworking Fluid Life: Predicting Productivity and Degradation via a Digital Twin (C4-AMR-Secker) Advanced Manufacturing Research Centre PhD Research Project Competition Funded Students Worldwide
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intervention models will lead to suboptimal decisions, potentially jeopardising the safety of a structure and increasing the costs. Traditional approaches to machine learning establish correlations between some
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also be joining the Leonardo Centre for Tribology, which is an active and friendly group. There are ~25 PhD students working on machine elements, tribology, lubrication, and sensor systems for wind, auto
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How does a molecule walk? Computer simulations of molecular machines in action School of Mathematical and Physical Sciences PhD Research Project Directly Funded UK Students Prof Sarah Harris, Dr
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all year round Details Kolmogorov–Arnold Networks rethink deep learning by learning functions on connections instead of neuron activations. This PhD will improve the methods for training KANs, grounded
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expertise in machine learning, soil microbiomes, microbial 3D printing and biophysics, our team has access to a broad spectrum of techniques and practical know-how. This is therefore an exciting opportunity
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treatment window may already have passed. Project Aim: This project proposes the development of an innovative approach that applies computer vision and machine learning to detect early signs of stroke through
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, advanced statistical methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and
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for attaining desired engineering properties. The project will combine physical modelling, experimental data, and machine learning to create a feedback loop that refines the material properties and manufacturing