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This doctoral research will concentrate on creating, assessing, and implementing sophisticated data analysis methods to address large-scale data challenges in aerospace or manufacturing systems. The aim is to discover concealed patterns, unidentified relationships, and other valuable insights for diagnostic and predictive solutions that improve system reliability, maintainability, and operational readiness. Recently, Big Data analysis has generated significant attention across academic and industrial sectors due to its potential to derive greater value from massive datasets. Such analytical approaches will enable the advancement of diagnostic and predictive techniques, ultimately refining maintenance strategies. Presently, machine learning stands out as the most viable technology for industrial Big Data applications. The successful candidate will collaborate with data analytics and condition monitoring specialists while joining our vibrant research community at Cranfield University.