18 atmospheric-modeling PhD positions at NTNU Norwegian University of Science and Technology in Norway
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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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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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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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-impact career paths in research and higher education, within academia, research institutes, or industry. We will employ a PhD candidate to perform research on development of an AI model that “understands
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. Developing innovative separation processes is expected to positively impact the circular economy and enable Sustainable Business Model (SBM) innovation. The current project's goal is to contribute
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seasonal emissions such as winter CH4 emissions, using AI tools to develop upscaling tools or upscale to circumpolar region, or using climate modeling such as the Norwegian Earth System Model to constrain
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designing, developing and evaluating systems and 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
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regulations that provides both incentives and constraints for the maritime energy transition and emission reduction. The research objective of the PhD is to develop models that capture the interaction between
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will develop models to understand non-equilibrium transport of orbital angular momentum in superconducting hybrid structures. This is part of an effort to determine the merits of superconducting
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models to resolve blade loads and structural responses under both operational and extreme conditions, including scenarios with partial out-of-water exposure Uncertainty quantification to ensure robust and