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the position. Your work tasks You will develop and validate digital-twin and optimization methods for electrolysis systems, working both independently and collaboratively with the group and with academic and
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are looking for candidates interested in developing new machine learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this position, you will
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be to develop wireless sensing and communication methods that are designed together with AI-based inference, rather than treating connectivity as a separate layer. Particular attention will be given
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Sensor Integration for High-Speed USVs This PhD project focuses on the development and validation of propulsion, control and sensor-integration methods for high-speed unmanned surface vehicles. The overall
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confidence-aware estimation of degradation, fatigue accumulation, probability of failure, and remaining useful life. These reliability metrics will be integrated into risk-based evaluation frameworks