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are seeking a highly motivated candidate to strengthen our enthusiastic research group, Data Assimilation and Optimization, working at the forefront of ensemble-based data assimilation methodology, optimization
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for spatiotemporal data (e.g., CNNs, LSTMs, Transformers, or Graph Neural Networks). Hybrid modeling: Experience with physics-informed machine learning or the integration of ML with data assimilation/multivariate
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assimilation improve the ability of Flow MRI to be used not just to visualise flow but to infer rheological behaviour directly from experimental data. This project will develop these capabilities by combining
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analysis, PDE-constrained optimization and optimal control, numerical analysis and scientific computing risk-averse and fractional models, digital twins and data-assimilating models, machine learning and
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for spatiotemporal data (e.g., CNNs, LSTMs, Transformers, or Graph Neural Networks). Hybrid modeling: Experience with physics-informed machine learning or the integration of ML with data assimilation/multivariate
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Speirs. The University of Aberdeen is home to the Aberdeen Computational Biology Forum, which brings together biomedical scientists, statisticians, computer scientists and physicists from across
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ideas, and assimilate the information into project design/interpretation. Lead and support implementation science studies. Support and engage in research efforts in community clinics and service
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The University of Southampton with support from the UKRI is funding until 30/09/2027 full-time work on the use of data assimilation for turbulent flows. You will be working under the supervision
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3 Dec 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Environmental science Geosciences Researcher Profile Recognised Researcher (R2) Established
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tables) and publish in peer-reviewed literature. Read literature articles, develop new ideas, and assimilate the information into his/her project design/interpretation. Dissemination of studies: Interact