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Challenge: Develop a climate model that enables climate optimized flight trajectories to be achieved at robust manner. Change: Improve the current climate model with broadening their geographical
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future decisions. Within this project, you will develop a modelling framework to investigate climate intervention approaches targeting clouds in the Arctic where temperatures are increasing rapidly
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Global climate models have provided warming predictions for several scenarios, the outcomes of which are primarily determined by assumed rates at which greenhouse gas reduction will be achieved
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knowledge into machine learning models to uncover mechanisms controlling plant resilience. The ultimate goal is to connect these findings with simulation models to predict how plants respond to environmental
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related to e.g. climate change, modelling and design of railway systems, multi-scale modelling of pavement materials and structures, reuse of materials, structures and parts of structures, assessment
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, the energy transition and sustainable reuse. Research themes include dynamics of structures, mechanics of materials related to e.g. climate change, modelling and design of railway systems, multi-scale
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on aerospace composite materials and structures with an interest on modelling and simulation of thermomechanical manufacturing processes using numerical methods as well as an affinity for validation activities
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feasible. This will enable us to improving climate models that can help assessing the effectiveness of climate mitigation and adaptation strategies. In this position, you will work on the forefront
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of an aggregate during consolidation. The modelling approach is intended to bridge the gap between the micro- and mesoscopic length scales. The finite element simulations of the manufacturing process are meant
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Fascinated by clouds? Motivated by tackling complexity in the climate system? Enthusiastic about physics? – Consider joining the MesoClou team! We invite you to apply for a PhD position on utilizing