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their analytical and numerical predictions with available experimental data. Applying the developed models to provide quantitative understanding of how the spatiotemporal profile of corticoids and androgens varies
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by comparing their analytical and numerical predictions with available experimental data. Applying the developed models to provide quantitative understanding of how the spatiotemporal profile
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estimation, and learning-based prediction models that anticipate the future motion of vessels seen in the radar data, based on the radar data, local geography and historical patterns. The methods
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signatures for data association and state estimation, and learning-based prediction models that anticipate the future motion of vessels seen in the radar data, based on the radar data, local geography and
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of maritime business models. As digital solutions replace manual coordination and increase data-driven transparency, the patterns of supplier relationships, contractual arrangements, and responsibility
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maritime AI business models Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is
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Fotograf Morten Hjertø 20th January 2026 Languages English English English The Department of Ocean Operations and Civil Engineering has a vacancy for a PhD Candidate in maritime AI business models
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– and building on recent advances in foundation models, neural model predictive control, and robotic world models – this PhD project will investigate principles and mechanisms for a shared autonomy
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, currents, water levels, wind, and ice. Machine learning models will be developed to forecast future variations in such dynamic conditions and to incorporate the operational state of the vessel into routing
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environment. Apply now if you are motivated to drive the project and eager to advance applied forest remote sensing. Main tasks Process remotely sensed data Develop statistical models predicting tree- and