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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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with experimentalists to validate predictions made by their machine-learning models and drive wet-lab discoveries. The candidate may also have opportunities to work with research software engineers
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-develop next-generation supply chain analytics leveraging predictive modeling, semantic models, AI, and natural language processing for advanced projects (e.g., semantic item classification, opportunity
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through microstructural characterization and comparing experimental observations with thermodynamic model predictions. Publishing your findings in peer-reviewed international journals and presenting
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rigorous quantitative description of phenomena predicted by theories such as K41 and Onsager, which still lack a full mathematical justification. The researcher will work on linear advection–diffusion models
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, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate ). We also began exploring how
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optimization of laser deposition coating processes using combined wire and powder feed, including numerical simulation of laser modelling, and process parameter optimization. Legislation and regulations: Law Nº
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intelligent decision architectures, predictive analytics, and adaptive computational models that can operate in dynamic, uncertain, and high-stakes project environments. The appointee will conduct original
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workflow that maps first-principles electronic-structure data onto predictive atomistic spin-Hamiltonians and device-scale dynamical models. The candidate will run high-throughput, relativistic DFT
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-driven methods provide excellent performance under low or cyclo-stationary regimes but struggle with highly dynamic and rapidly varying conditions; conversely, model-based state observers ensure robustness