25 linked-data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"IDAEA-CSIC" PhD positions at Cranfield University
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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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. This project aims to develop a novel FEA-based approach that incorporates realistic energy input linked to arc physics and equivalently accounts for the effects of liquid metal convection on
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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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drainage, excavation, drought or rewetting. Combining soil classification, LandIS legacy data, field sampling and predictive mapping, the researcher will identify where these soils occur and determine how
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postharvest drying energy demand. Combining applied mycology, food safety modelling, precision agriculture and Net Zero energy systems, the research will deliver energy-efficient, data-driven grain
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repeated environmental disturbance. The data will inform a dynamic model linking weather exposure with fungal retention, recovery, release and establishment. The research will provide new mechanistic
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) batteries for transport systems. You will combine hands-on experiments with physics-based data-driven modelling to understand how Li-S batteries perform in real applications and develop suitable battery
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turbines. The research will combine physics-based modelling, artificial intelligence, structural health monitoring and real-time data integration to improve asset reliability and predictive maintenance
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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