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into the learning mechanism. The integrating should enable to guarantee certain properties of the learned functions, while keep leveraging the strength of the data-driven modelling. Most of, if not all
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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We are looking for a highly motivated candidate to pursue a PhD programme titled " CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition ." This research
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, Artificial Intelligence, Data Science, or other relevant STEM disciplines. Experience in one of more of offshore systems, sustainability assessment, programming, data analysis or AI modelling would be
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provides rich datasets with well resolved spatial and temporal measurements. The overall aim of this PhD project is to develop the next generation of advanced data analysis and characterisation methods for
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internal data but often disrupt the process, alter the thermal fields, and risk damaging the part during fabrication. Finite element analysis (FEA) models, while capable of delivering detailed
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experience in experimental design, quantitative data analysis and dynamic modelling, alongside research planning, data management, scientific writing and presentation. These skills will support careers
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, ecology or related disciplines. Experience of, or a strong interest in, fieldwork, laboratory analysis and quantitative data analysis (e.g., R) would be beneficial, though full training will be
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capabilities in thermal systems analysis, mass transfer modelling, computational simulation, data analytics and experimental validation, alongside applied mycology, and food safety risk modelling
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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