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Field
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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to gain insights into complex systems and inform decision-making Design and evaluate scenarios that focus on energy systems and structural change, assessing their potential impact Develop and evaluate
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our
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and computational modeling to understand complex biological processes. Experience in statistical modeling, machine learning, or analysis of spatial or high-dimensional biological data is considered
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of systemic neurosciences: single cells to complex systems system analysis to mathematical modelling perception and cognition to mind and neurophilosophy biology to technical solutions Additional support is
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research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle Analysis
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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
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, using equipment like 3D printers, furnaces, centrifuges, and microfluidic devices. Meticulous data recording and analysis are essential, as the project combines practical engineering with fundamental
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uncertainty quantification for robust structural design, particularly for complex aero-engine systems with limited experimental data. Recent work by the University of Southampton developed a novel data driven