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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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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 genes underlying responses
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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. 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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involve applications of the existing framework and advancement in the interface towards integrated assessment and energy system models for scenario analysis. The selected candidate will join a team of
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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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a PhD position vacant from March 2026, for applicants who wish to obtain the degree of Philosophy Doctor (PhD). The position is affiliated with the research group Electromechanical systems, within
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understanding of the advantages and disadvantages of pyrochemical and hydrochemical recycling routes. Perform thermodynamic simulation and modelling activities to support the experimental design, enhance