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mechanical wear and electronic errors pose risks to efficiency, increasing costs and resource waste. This Ph.D. project aims to address these challenges by advancing fault diagnosis and prognosis (FDP
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This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and
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, impacting everything from cardiovascular to mental health. Despite this, women face significant delays in diagnosis and treatment, often experiencing a trial-and-error approach due to a lack of comprehensive
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& Statistics Project description Unmanned Aerial Vehicle (UAV) e.g., drones are increasingly used for equipment anomaly and fault detection. When the drones are employed to take images, the quality of the images
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thematic areas: Control systems, computational intelligence and machine learning, autonomous systems, optimization and networks, embedded and real-time systems hardware and software, fault diagnosis, cyber
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profile: • Very good degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault