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for anomaly Detection and diagnostics: Leveraging state-of-the-art machine learning and deep learning models for automated fault detection, classification, and time-till-failure prediction. This will involve
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“Multiscale modelling of soil-structure interaction for renewable energy applications”. An improved understanding of soil-structure interface behaviour can lead to significant cost savings for offshore wind
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-fueled engine, power converters, and a battery energy buffer. Key tasks will include developing system-level models, optimising energy management, and coordinating power flow between subsystems to maximise
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diseases, but is frequently misunderstood, forgotten, and missed. As a toxic proteinopathy that leads to progressive fibrosis, it offers a powerful model for studying common pathways in CKD and represents a
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Classification Title: Post Doc Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science or a related field. Working experience with large language models
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. Clinical studies have demonstrated that hereditary neuropathies can also involve muscle pathologies, complicate diagnosis and hamper therapy development. We have developed advanced in vitro cell models
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• Strong quantitative and programming skills; experience with seismic data analysis or numerical modelling is highly desirable• Excellent written and verbal communication skills• Ability to work
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Foundation Models initiative . The proposed starting date is 1 September 2025 or soon thereafter. The appointment will be made for a term of three years at a competitive salary and will follow the PhD study
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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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research focus will include some of the following topics: Advanced sensor fusion and multimodal AI models for robotic intercropping. Self-supervised learning will generate multimodal agricultural pre-trained