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epidemiology, and working with methods like random forest and targeted learning, the candidate will contribute to the development of interpretable survival models and doubly robust estimation methods
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models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
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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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that explain how humans learn, adapt and stabilise navigation behaviour in urban environments. The project will combine methods from transportation science, artificial intelligence, computational neuroscience
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models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
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competence You have Completed an academic degree at the candidate or master level in a STEM discipline (e. g., Chemistry, Biology, Physics, Computer Science, Human-Computer Interaction, IT Product Development
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technologies Research Field Computer science » Computer systems Computer science » Computer hardware Researcher Profile First Stage Researcher (R1) Application Deadline 11 Aug 2026 - 21:59 (UTC) Country Denmark
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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
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. linguistic bias), specifically the effects of grammatically un/gendered languages and the masculine default, on gendered representations using corpus linguistic methods; reveal how AI tools echo and reinforce