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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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analyze particle precipitation from low-altitude spacecraft, in conjunction with particle and wave measurements from near-equatorial spacecraft, and theoretically model electron precipitation driven by
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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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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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questions for both Biogeography and Quaternary Palaeoecology, and the answers provide the basis for predictions of ecosystem and species response to future climatic change. We are looking for PhD candidates
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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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predictive control, optimization-based decision frameworks, and data-driven performance modelling. The overall goal is to develop computational methods that enable efficient and intelligent operation of wind
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. Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms). Integrating these predictions
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processing [1–3]. The experimental results obtained will be combined with a theoretical model enabling the prediction of equipment damage and service life, with the goal of optimising their operation and
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of pathogens, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modelling of pathogen