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Field
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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profile Completed university degree (Master’s) in biology, geosciences or related areas Experience in morphology, neuroanatomy, and paleontology of turtles is desired Expertise in the analysis of digital CT
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creep properties, liquid lithium compatibility, high thermal conductivity, and low neutron absorption. Thus, reliable W/V joining is critical for system operability. While W/V joints have a lower
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workflows for descriptor based microstructure reconstruction to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property
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Element simulations (e.g. pushover analysis and/or incremental dynamic analysis). Moreover, the project aims to verify the ductility requirements with full-scale experimental results and explore
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of the projected weather parameters into the RESkit framework and subsequent calibration and validation of the output Global simulation of the electricity output under various climate change scenarios Analysis
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, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and/or time series analysis is a plus. The position requires
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groups of Guinea baboons that are part of a community of more than 400 individuals. We combine behavioral observations, analysis of ranging patterns using GPS data, population genetics, acoustic analyses
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languages, artificial intelligence, and security, with a focus on tools and techniques for constructing reliable, efficient, and secure software. General areas of research include: Artificial intelligence