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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 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
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year before the position expires, you will be offered an interview to clarify your future career. Description of the PhD position: The PhD research will focus on mathematical / computational modeling
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for resilient manufacturing systems. This topic will build upon existing theory on modular and reconfigurable manufacturing systems and develop methods and model-based approaches to design and evaluate resilient
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disease models. The emphasis will be on the communicative potential of these vesicles in the gut-brain-metabolic axis. The LHMI group operates a state-of-the-art molecular biology laboratory and maintains