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laboratory. The candidate will benefit from the expertise in numerical simulation and bioinformatics available at the L2C and the IBMM. The IBMM will produce the initial glycoproteins for calculations using
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of Quantum Chromodynamics in scenarios characterized by multiple energy scales. The expected results will help refine phenomenological models, improve Monte Carlo simulations, and contribute to a better
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- research experience in the evaluation of global wave reanalysis and integration of topographic and bathymetric datasets, as well as experience in the implementation of XBeach and SWaN models. Preferential
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conducting simulator-based experiments, collecting and analyzing human performance and psychophysiological data, and developing models of human–machine collaboration for safe and efficient navigation
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Simulation) will support a one-year applied research project and evaluate a mobile DC microgrid for military tactical applications. The role involves developing detailed power system models in ETAP and MATLAB
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models developed as surrogates for the computationally expensive KMC simulations. The existing workflow will be extended to include the additional photo(electro)chemical variables. Where to apply Website
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to carry out high-performance numerical simulations using our in-house CFD code, extract physical insights from simplified flow models, and characterise synchronisation thresholds and the robustness
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processes, multimodal data fusion, physics–ML hybrid modelling (from CFD to atomistic simulations), and AI-assisted hypothesis formulation. MSCA Doctoral Candidate eligibility criteria Applicants must comply
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and validation of a predictive pipeline for excipient–biologic interactions Integration of experimental SAXS data with AI-driven structural modeling to predict oligomerization behavior and excipient
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-learning–based segmentation, classification and tracking for microbes and microgels in phase-contrast and fluorescence images Optimise these models and pipelines for real-time performance and integrate them