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PhD project: Modelling Resilience of Water Distribution Networks Supervised by Rasa Remenyte-Prescott (Faculty of Engineering) Aim: To develop an modelling approach for assessing water network
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PhD project: Modelling Reliability and Resilience of Hydrogen Systems for Improved Safety and Sustainability Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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record, in many areas of breast cancer including pathology; cell, molecular and radiation biology/radiotherapy; medical oncology/chemotherapy; translational oncology; clinical trials; pre-clinical models
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modelling framework to predict key thermal hydraulic parameters for boiling flows within complex geometries at high heat flux conditions, relevant to the engineering design of thermal management elements
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Programming Intelligent Modelling and Analysis Mixed Reality Lab Lab for Uncertainty in Data and Decision Making Visualisation and Computer Graphics Responsible Digital Futures The studentships available
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on atomic scale, requiring the development and study of ever more realistic model systems. Single atom catalysts, where the catalytic site contains only a single metal atom supported on a heterogenous
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device