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performance. This topic is based on a Sapere Aude Research Leader grant from the Independent Research Fund Denmark: Optimizing Human-AI Interaction: Integrating Domain Knowledge into Causal AI Systems: Causal
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=ab369eed-9005-4b04-9b12-66e400036e1c ). The project aims to build fundamental knowledge on the biology and environmental tolerance of the lumpsucker (Cyclopterus lumpus ) — a culturally and ecologically
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optimization and enable automated diagnosis of performance-limiting factors and suggest optimization strategies. The project will be part of the DFF Sapere Aude project, and research stays abroad are part of
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sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued
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), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued. Mathematical skills: Competence in mathematical modeling of dynamic systems and
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knowledge exchange with industry and academic partners involved in the TRANSITION project and play an important supporting role in the deliverables of IEA Wind Task 50 on Hybrid Power Plants and IEA Wind Task
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of millions of combinations of control parameters, determining the optimal values to maximize stability, efficiency, and dynamic performance. The ideal candidate will have experience or an interest in
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, current methods are either static, rely on heavy offline training, or fail to adapt to changing environments. This PhD project will develop intelligent software agents capable of autonomously optimizing