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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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conditions. The specific aims are: To optimise large-scale production of a high-value carotenoid compound that is naturally released in nanoparticle form by a marine alga. Develop a mechanistic understanding
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a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse
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on these materials, which will be used to implement high frequency and high efficiency IVRs for HPC applications. Objectives:-Fabrication, characterization and modeling of the composite magnetic materials.-Modeling
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models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel typically possess complex microstructures across various length
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competences within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and
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contributes to the improvement of climate prediction models. The Atmospheric Chemistry and Atmospheric Microphysics departments are looking for a committed doctoral student to carry out this project. You can