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and difficult to anticipate. Predicting the spatio-temporal dynamics of these changes generally relies on empirical models, most of which project correlational relationships between species occurrences
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derived spheroids Develop predictive model of drug response by comparing 2D to 3D cellular systems Testing and validating the relevance of such models in patient tumour specimens Support and preparation
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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in the prediction and modelling of extreme flood events? Do you want to understand how
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is to move beyond traditional “check-after” approaches and instead predict and prevent errors while the radiotherapy treatment is being delivered. The candidate will build upon this existing prototype
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types will change under different climate change scenarios based climate projections. This framework will be ultimately included in a flood prediction model, which will be developed within the VIDI
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anticipating crises. Current landslide prediction models, based mainly on rainfall thresholds, become ineffective in the presence of snow cover. Snow acts as a temporary reservoir, storing precipitation before
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to combine high-throughput metabolomics with 3D cell culture models Perform large chemical and genetic studies in cancer cell lines derived spheroids Develop predictive model of drug response by comparing 2D
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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and observation models to reflect real-time changes in environmental conditions, enabling more accurate predictions of adaptation impacts and thereby supporting a better-informed, resilient decision