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modelling. ClampIT builds on the experience from the DynaLoad project and brings together a strong consortium covering the entire transformer value chain, including: Sensor and material suppliers: COMEM
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selection criteria You must have a relevant Master's degree in [subject area] or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained
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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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of the research project are (i) Identify different climatic areas relevant to the study and characterize weather conditions to be used as boundary and initial conditions in modelling; (ii) Develop thermo-hydro
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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 population and environment (air, soil, and groundwater). A schedule optimization problem has emerged in this context, where tasks correspond to contaminated sites to be cleaned, while managing risks
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use the model species thale cress (Arabidopsis thaliana) as a resource to help identify the molecular mechanisms and genes underlying responses to altered temperatures and parasite (co-)infection. We
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cell walls, which have been implied in responses to the two parasites. We will also use the model species thale cress (Arabidopsis thaliana) as a resource to help identify the molecular mechanisms and
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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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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