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model that explains lattice distortions and branching mechanisms. (4) Analyze experimental data using advanced computational tools and present results in research meetings and scientific publications
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by fostering large-scale, interdisciplinary collaborations through an original and collegial organizational model. They aim to stimulate novel collaborations and contribute to the emergence
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and parametrizations that lead to improved, energetically consistent, climate models. Close collaboration with the other research areas of the CRC is expected, and more information can be found
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Geosciences Experience and skills · You have a strong interest in terrestrial ecosystems modelling, vegetation demography, plant physiology, and climate change. A background in forest engineering
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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-based modelling, quantitative resilience assessment, and risk analysis to simulate and optimise resilience strategies. The framework will be tested and refined through pilot studies in collaboration with
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to distributed energy resources, enabling energy sharing, reducing grid congestion, and enhancing sustainability. The PhD project will focus on the governance models adopted for energy hub platforms. These include
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technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using machine learning models. You care deeply about privacy and are keen
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Design and evaluation of multi-functional Blue Green Infrastructure under climate change Award Summary Fully funded Studentship: fees, annual living allowance (£20,835), training support grant
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d'étudier comment l'adaptation des espèces sauvages apparentées aux cultures aux environnements secs pourrait être informative sur la réponse du maïs à un climat plus extrême