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of these phenomena, and how they affect the performance and operation of cells, using advanced mathematical modelling in the open-source simulation platform OpenFOAM. The main supervisor of the candidate will be Prof
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application process here. About the position The Department of Materials Science and Engineering (IMA) at the Natural Science Faculty, has a vacancy for a position as PhD candidate related to modelling
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capabilities within the underwater domain, and to ensure that a unified modelling approach can operate across robot embodiments – air, ground, and marine. Achieving this requires new simulation tools, scalable
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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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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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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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simulations can support data augmentation. Key deliverables of this project will be a multi-target radar tracker that learns to utilize radar targets’ amplitude signatures for data association and state
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. Experience with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage. Experience and abilities
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models to enhance learning through AI technology. A part of this work is also to consider opportunities for innovation related to start-up companies. The approach followed encapsulates Design-Based
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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