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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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drought early warning and monitoring system for large-scale river basins. The project will explore both data-driven and model-based approaches for drought predictions, paving the way for a continental high
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machine learning to rich molecular data and uncover the molecular basis of IBD. The successful candidate will build prediction models from high-dimensional molecular measurements, with a particular focus on
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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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strengthen explanatory and predictive models of surveillance data. Job Description and Research Objectives At the Capital Region of Denmark, Nordsjællands Hospital, Region Hovedstaden, DETECTIVE is looking
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leakage and the project ACE Water, in the topic degradation in LTEL and HTEL stacks and developing lifetime models, life-time predictions and the validation of them. You will be expected to contribute
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reliably assess fatigue damage and predict remaining lifetime, enabling proactive maintenance strategies that extend service life and reduce CO2 emissions. Through this PhD scholarship, you will contribute
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is the development of hybrid models that combine our integrated national model of Denmark with AI-based methods to improve predictions of floods and droughts. We seek to enhance our ability to predict
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in-line or at line spectroscopic tools Large-data, modelling and prediction of food and ingredient processes. Understanding of biological production systems and their use, and with an emphasis
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technologies Development and utilization of high throughput methods for characterizing and quantifying the physicochemical behavior of food macromolecules in complex matrices. Modelling and the use of machine