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Field
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, Ultrasound and Vibration, Aircraft Structures, Damage Assessment, Structural Health Monitoring, Structural Health Prognosis, Bayesian Statistics, Machine Learning Informal enquiries prior to making
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
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] Cross, E. J., Gibson, S. J., Jones, M. R., Pitchforth, D. J., Zhang, S., & Rogers, T. J. (2021). Physics-informed machine learning for structural health monitoring. Structural health monitoring based
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orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that
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machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite missions (e.g., CO2M, TANGO, Sentinel-4/5). Your research will contribute directly to monitoring global efforts
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-Intrusive Load Monitoring (NILM) can bridge this gap by turning whole-home readings into appliance-level information, with studies showing meaningful efficiency gains for households. However, deploying NILM
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interaction, signal processing, data science and machine learning. The successful candidate will gain expertise at the intersection of structural health monitoring, railway engineering, and advanced artificial
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for future flight. You will develop a strong expertise in computational mechanics, structural health monitoring and machine learning with a particular focus on fundamental aspects that can have far-reaching
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knowledge with statistics, machine learning, Deep Learning and AI are an advantage • Good knowledge of the English language LanguagesENGLISH Research FieldEnvironmental science » Ecology Additional