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Modelling post combustion amine CO2 capture plant School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin Hughes
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) and the University of Warwick seeks to develop flexible digital twin models that will enable novel, integrated solutions to the decarbonisation of heating and cooling on large industrial and commercial
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signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health. You will develop and apply cutting-edge techniques in: Signal processing
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29.04.2021, Wissenschaftliches Personal This PhD position is in the field of resource management for wireless network that leverage “digital twins” modeling aspects of the physical (such as user
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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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: 30 August 2025 Apply now As part of the EMBRACER project external link , you will use advanced models integrating our climate system to human behaviour to study potential scenarios of what could happen
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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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in a discipline related to “Greenhouse gas emissions modelling; Reduced-complexity modelling of the land surface carbon cycle; Climate modelling; Climate mitigation modelling”; demonstrate expertise in
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of the immune system in retinal degenerative disease. We utilize induced pluripotent stem cells, human donor tissue and mouse models of retinal degeneration to study the role of monocyte derived macrophages in
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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a