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: Computational, Quantitative, and Predictive Modeling of Root Systems. This position emphasizes integration of phenomics and other -omics data into predictive frameworks. Research areas may include: Structural
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based on Machine Learning (ML) emulators have taken the weather predictions research by storm, as they run faster and use less energy than traditional approaches: numerical models based on physical
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. The functional relevance of these biomarkers will be investigated using both in vitro and in vivo models, as depicted in the publications of team. Selected Publications from the Team 1: Dousset L, et al
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during these experiments will be used to calibrate a numerical model of PFAS fate in soils. The predictions from this model will then be compared with PFAS concentration measurements in leachate collected
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physics-informed machine-learning models for binding affinity predictions in rational small-molecule drug design. The models will allow prioritisation of candidates from hit discovery through to lead
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, progression, and treatment outcomes. Skills in applying causal inference, survival analysis, and longitudinal modelling to link clinical and biological data. Expertise in predictive modelling and AI
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, Purpose of the Job We are looking for one Research Associate to work on the development, implementation and testing of predictive control algorithms for the optimal coordination of available multi-energy
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develop predictive, pharmacodynamic and response-monitoring biomarkers. You will have expertise in preclinical models of cancer (patient-derived and immune-competent models) and be well-versed in drug
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NIST only participates in the February and August reviews. The fire modeling community is actively working to develop the tools needed to quantitatively predict material and product flammability
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Post-doctoral position (M/F) for testing drought-based BEF relationships at CEFE Montpellier, France
) Carry-out additional simulations with the Phoreau model to test the effect of tree diversity on forests' resistance to droughts. ii) Analyse biodiversity-drought resistance relationships, across a