16 computer-vision-and-machine-learning 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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aspects of machine learning. Applications include improving the efficiency of data assimilation methods and understanding why and how deep learning works. Applicants should have, or expect to achieve
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to the design of aircraft, wind turbines and medical devices, and for modelling the environment. Remarkable advances in computing driven by the exponential miniaturisation of transistors (Moore’s law) have
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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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to build molecular machines and new materials. The ability of their subcomponents to undergo large amplitude displacement, such as macrocycle shuttling in a rotaxane, make them ideal structures
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farms at relatively close proximity can be relevant when considering their annual energy production. This project will examine the uncertainty of various types of numerical models, from fast-computing
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-free stipend based on the UKVI amount (£20,780 for 2025-26). We expect the stipend to increase each year. This studentship is related to a multi-institutional EPSRC Programme Grant “AMFaces: Advanced