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the development of numerical models. Metrics to quantify damage detection effectiveness, such as Probability of Detection (POD) and Model-Assisted POD (MAPOD), will be identified to develop a figure of merit
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: (i) the rarity of extreme events, which renders classical statistics inadequate; (ii) the uncertainty inherent in cascading effects; and (iii) the lack of confrontation between numerical models and
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experience or knowledge in one or more of the following areas are also a merit: Space physics Plasma physics Computational physics Applied mathematics and modelling Numerical methods for partial differential
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macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie
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of electrochemical effects into numerical and theoretical models describing the flows within LMBs. These flows, driven by magnetohydrodynamic or thermal phenomena, can become unstable and lead to a short circuit of
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trips, plus an elective course. Examples of elective courses could include aqueous geochemistry, geomorphology, soils, glaciology, GIS, or numerical modeling. We are seeking candidates who can demonstrate
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meteorological data Numerical oceanographic modeling Development of a warning system for extreme sea levels Analysis of results, writing scientific papers Where to apply E-mail teodora.rogosic@unist.hr
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successfully applied to numerous protocols in the literature, providing security proofs or revealing new attacks. However, these formal (or symbolic) models do not allow for the modeling of probabilistic
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and numerical methods, collaborate with top universities, secure government funding, and actively participate in CMIP6 and the upcoming CMIP7 using the in-house Taiwan Earth System Model (TaiESM
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centrifuge experiments. Integrate findings with numerical models for validation and deeper interpretation. Develop innovative experimental apparatus (SolidWorks proficiency is a plus). Disseminate results