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is both experimentally realizable and accompanied by a digital thermal model suitable for real-time prediction and control. The two positions are closely coupled. One focuses on physics-driven thermal
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will also be integrated into the wider CENSEMAT research environment at Aarhus University, allowing computed models and predictions to be tested directly against advanced experimental characterisation
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Do you enjoy finding solutions to integrate and analyse large data sets of biodiversity dynamics and their drivers? Are you creative and able to couple various data flows and integrated modelling
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team. The publication pipeline includes papers on main trial outcomes, secondary outcomes, moderators of treatment effects, and prediction based on baseline data. Research tasks The main tasks will
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possible thereafter. The research to be addressed AI has been applied to Software Engineering for some time, and in areas such as software effort estimation, defect prediction, and software development in
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or bacterial or parasitic) as well as their metagenomic sequence datasets available within the EUPAHW- JIP2 - SOA23 consortium and/or in public databases with an overall aim of predicting and preventing