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Field
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, surgery planning with patient data for surgeons, real-time remote guidance for maintenance in industrial plants, and iterative design simulation for architecture and engineering. However, its wide adoption
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, while simulations are subject to error due to uncertainty in nuclear data and unresolved physical processes e.g. thermal expansion and fine-scale inhomogeneities. Generating independent simulation
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a result of microphase segregation. Low crosslinking regions can be weakly attached to the rest of the paint making them prone to degrade. This project will use state of the art molecular modelling
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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heavier than their fossil fuel powered counterparts. A framework that can accurately model complex dynamics and generate projections for future scenarios is essential for understanding the impact of changes
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simulations to model this process and, in conjunction with ongoing experimental studies, obtain design rules for the optimum crown ether, lithium counter-ion, and solvent, which will lead to enhancements in
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In this position, you will work on microscopy-integrable measurement technologies used to study three-dimensional cell culture models of breast cancer tissues. This PhD candidate position is
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to enhance the UK’s energy system resilience through a whole-system analysis approach. Building on the proven WeSIM model, RENEW will upgrade its capabilities to incorporate electrified district heating and