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learning models to predict ion-exchange isotherm parametersIntegration of predicted parameters into the CADET chromatography simulation framework Simulation and analysis of batch and gradient elution
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state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational campaigns. Key responsibilities Design and execute in silico protein and
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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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applications. Grid-interactive efficient buildings rely on emerging digital and cyber-physical systems to optimize HVAC operations for both energy efficiency and demand response. While Model Predictive Control
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—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from
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as predictors of plant function and community assembly --- into predictive computer models of terrestrial ecosystems, land-atmosphere interactions, and the Earth System. Field of Science: Earth Science
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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
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metadata from plant microbiome composition, including plant part, microbiome compartment, and host taxonomy Cross-study evaluation of microbiome-based prediction models to assess robustness and
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to data analysis, feature engineering, model development, evaluation, and documentation, while progressively gaining exposure to production systems, client-facing work, and modern AI practices across
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decision support Analysis of large-scale geospatial, sensor, and remote sensing datasets (e.g., multispectral, hyperspectral, LiDAR) Predictive modeling for crop performance, resource efficiency, and climate