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organization. About the position The Nansen Centre has long expertise in data assimilation (DA) and climate predictions, initially introducing the Ensemble Kalman Filter (EnKF) data assimilation method in
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cost of conventional numerical weather prediction systems, opening new possibilities for large forecast ensembles and event-based climate attribution. The PhD researcher will evaluate the predictive
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the high latitude ocean. A tool for both understanding and prediction of these processes is the next generation of the NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS
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logistic regression, Poisson regression, Cox proportional hazards models, Kaplan-Meier analyses, generalised estimating equations and diagnostic prediction analyses. § Interpret findings within the context
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researcher to conduct education and research related to the development of AI-based subseasonal-to-seasonal prediction models. https://www.jst.go.jp/k-program/program/kaiyou4.html [Work content and job
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, ensemble modeling strategies. Run large‑scale structural predictions and interface scoring on HPC infrastructure. Rank nanobody candidates using structure‑based affinity and interface
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of organelles into mixed sub-populations, in which all proteins are identified by mass spectrometry. Based on the distribution of marker proteins within these sub-populations, it is possible to predict
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for structural biology. This project sits at the intersection of X-ray scattering and deep learning, aimed at integrating experimental data to predict protein ensemble structures. As an Empire AI-funded fellow
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
to develop and learn novel representations of the coupled ocean-atmosphere dynamics ocean models. For accurate climatic predictions, it is essential to have plausible forecasts of the future ocean state
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
observation-driven paradigms to develop and learn novel representations of the coupled ocean-atmosphere dynamics ocean models. For accurate climatic predictions, it is essential to have plausible forecasts