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the efficiency. The outcomes will be to validate its efficacy against frequent unstable events, handling contingencies, accommodate protection technologies by tokenizing energy-based control and modeling
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algorithms and systems that enhance the robustness, flexibility, and adaptability of autonomous systems. Address multi-agent operations, where interactions between agents are intricate and interconnected
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education and knowledge dissemination. Job description We seek PhD students that will contribute to new generations of scalable, model-based tools for cyber-physical systems based on a mathematical sound
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simulation framework to model the coupled USV-UUV system, enabling safe experimentation before field deployment. Field validation: Conducting field experiments (e.g. in a harbor and offshore test site) where
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and European companies and international academic partners. The AI4OR group focuses on solving complex problems, which require high-level modelling, data analysis and management capabilities as
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and AI-based segmentation, with a particular emphasis on inter-vehicle collaboration. The overall goal is to develop robust, scalable methods for detecting and classifying structural anomalies (e.g
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about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its
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limitations of current EMG-based techniques, particularly in dynamic movement tasks. The PhD student will focus on the design, development, and validation of the HD-sEMG/ultrasound system. This includes
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, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within
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will conduct sampling, and apply experimental methods such as metagenomics and metatranscriptomics, linked to soil and emission data to help create predictive models. Within a broader framework, your