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Description The aim of this research is to enhance the durability and fire resistance of veneer-based wood products by developing and optimizing a sustainable wood densification process. The study seeks
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be used to gather transport, storage, and BWRX-300-specific waste forecasts. These foreground inventories will be integrated with Ecoin- vent background processes to construct life cycle datasets
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-based control of multilayer electrospinning. The task of the PhD student is constructing a scalable, multiparameter model, which maps online observable process parameters (e.g. spinneret voltage, flow
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model, which maps online observable process parameters (e.g. spinneret voltage, flow rate etc.) to nanofiber product quality (e.g. morphology, diameter variance, all of which are only observable offline
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its vibrant food, tech, and music scenes. Selection process The application procedure consists of two stages. Stage 1 If you are interested in applying for this PhD position, please contact Dr Tarmo