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1st February 2026 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate PhD Candidate in Underwater Foundation Models Apply for this job See
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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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students from all over the world. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning engines, and reinforcement learning—can be adapted and
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marine technology, together with more than 60 PhD students from all over the world. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning
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the vessels to identify and utilize quiescent periods during harsh weather conditions. To this end data from navigational radars and other relevant sensor channels will be used as input to models that can be
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on optical transmission through falling snow and the models we have are inaccurate. By conducting experiments in Arctic weather over a longer period of time, at different geographic locations, we hope to build
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models to enhance learning through AI technology. The PhD fellow will engage with developing and evaluating models and agents, as well as, multi-agent networks that support the human learning and improving
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Operations research group is dedicated to developing and showcasing digital twin models for selected vessels through extensive ship performance and navigation data. The position is funded by the TwinShip
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the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create interpretable, data-driven observers that enable physically grounded perception and control for robust
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explainable physics-informed RNNs for autonomous navigation and neural observer design within the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create