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. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in
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stability, and computational efficiency. It is expected that the coding will be done with an open-source programming language. The field experiments have the aim of validating the modelling; they will involve
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-party computation) to safeguard data privacy and model security during training and deployment. Deepfake detection: Develop advanced approaches to secure AI-driven media verification systems and prevent
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floating wind energy with a special focus on nonlinear hydrodynamic fluid-structure interaction and the interaction between the hydrodynamic and rotor-based motion response. Computational Fluid Dynamics will
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-party computation) to safeguard data privacy and model security during training and deployment. Deepfake detection: Develop advanced approaches to secure AI-driven media verification systems and prevent
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in