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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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). The project investigates how machine learning (ML) can be used to enhance the modelling of boundary layers in industrial CFD simulations, where complex geometries and computational constraints limit near-wall
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About the project: From Brittle to Ductile: Machine Learning 3D Fracture Simulations for Extreme Environments Supervisor: Prof, James Kermode, University of Warwick Develop cutting-edge machine
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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A Human-Factors Investigation of Automation, Decision-Support and Machine Learning in Clinical Decision-Making Tasks. This PhD project is based within the Human Factors Research Group in the Faculty
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About the project: Supervisor: Professor Nicholas Hine, University of Warwick This project uses cutting-edge computational and machine learning methods to accelerate catalyst discovery for fuel cell
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EPSRC ReNU+ CDT PhD Studentship: Physics-informed machine learning for deep geothermal systems under uncertainty. Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours