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together with the new numerical model to compare cooling rates in the various available sections of oceanic crust. These, together with new data from natural samples from selected areas, will be used
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Description Open one or two year Postdocs positions on Surrogate Models for Uncertainty Quantification (UQ), at the Centro de Investigación en Matemáticas (CIMAT-SECIHTI, México). We are a UQ research group
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, Python, or C++ is required. A strong interest in numerical modelling, sound, signal processing and programming is expected. Additionally, very good command of German and English as well as experience with
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primarily focus on one or more of these parts. The successful candidate will develop numerical tools and/or theoretical models to model and simulate the behavior of a group of agents capable of chemical
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Research FieldPhysicsYears of Research ExperienceNone Research FieldTechnologyYears of Research ExperienceNone Additional Information Eligibility criteria Creation of models Analytical calculations Numerical
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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
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, advanced materials, and innovative concrete strengthening solutions. Our work combines experimental investigations, analytical modelling, and numerical simulations to develop and validate novel reinforcement
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ingredients for Earth-like magnetic fields on millennial time scales in dynamo models. The research activities are two-fold. First, the candidate will run numerical dynamo simulations with various combinations
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; Couple the model to a 1D physical model (GOTM) through the FABM framework; Validate the coupled model using published and newly gathered observational data; Conduct numerical experiments to understand
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experience in hydrological or Earth system modeling, with emphasis on process understanding and prediction. Strong background in computational sciences, including numerical methods, high-performance computing