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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. •Specialist training in AI, machine learning, and digital engineering. •Collaboration with academic and industry experts for technical insight and mentoring. •A supportive research environment focused on both
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, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in
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Engineering (PhD) Eligibility: UK Students Award value: Home fees and tax-free stipend £20,780 - See advert for details Project Title: Machine Learning and Optimisation-Based Intelligent Substation Design in
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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modelling and simulation techniques and software packages would be an advantage. Programming skills in languages such as Python, C++, MATLAB, are desirable, as is an awareness of machine learning or other AI
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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the field of Modelling and Simulation (M&S), with a focus on biomechanics, biofluid dynamics, and machine learning applications in healthcare. Specifically, it addresses the simulation of cerebral blood flow
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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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of this proposal is to improve their System 2-like abilities by systematically integrating reinforcement learning techniques, encouraging models to reason more deeply when required. Applicants should have, or expect
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities