21 machine-learning-and-image-processing PhD positions at The University of Manchester
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Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation
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scattering with computer modelling such as molecular dynamics simulations and AI-assisted data mining. The new technical capabilities will help bridge the current gap in biocide development, i.e., to link
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useful background for candidates would include continuous-time stochastic processes, martingales, Brownian motion. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s
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, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic
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simple identification of nuclear material even when the typical signatures of the materials may be unavailable. X-ray imaging is commonly used to image concealed objects but x-rays are attenuated in
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Mativenga (UoM), has extensive expertise in laser materials processing. Dr Chu Lun Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and
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of reinforcement learning or agent-based systems. LanguagesENGLISHLevelExcellent Research FieldComputer science » Computer systemsYears of Research Experience1 - 4 Additional Information Benefits • Full funding
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to also improve and scale the process. We have made major contributions in this area, including the use of Machine learning to discover new cryoprotectants [Nature Communications 2024, 15, 8082
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sluggish diffusion kinetics of HEAs make them excellent candidates for resisting oxidation and corrosion in high-temperature steam. Guided by thermodynamic modelling and machine learning, we will identify
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Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and will support the project by assisting with the in-process monitoring. We expect