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We invite applications for a PhD project focused on fundamental research into novel low-emission ammonia combustion/oxidation processes. This position is based within the Faculty of Engineering at
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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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manufactured using plasma spray and mini-combustion flame spray and examined in SEM/EBSD and tested in a burner rig and furnace thermal cycling. As a part of a CDT cohort, you will have access to tailored
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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
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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