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between research institutes and industry partners, combining experimental and numerical expertise. This position is part of the ANR DYNATERRE project, which focuses on the static and dynamic behavior
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and Ar-Ar geochronology, fission-track and (U-Th-Sm)/He thermochronology, vitrinite reflectance, and thermal history models. New relational data models data for incorporating methods such as include
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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Biochemistry, Molecular/Cell Biology, and/or BioEngineering documented by peer-reviewed publications Skills in a broad range of methods in the fields of Biochemistry, Molecular/Cell Biology, and/or
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- Develop original numerical methods for facility simulation in presence of expansion waves - Demonstrate improved estimates of rate constants for two-temperature models - Contribute
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology
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challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non
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responsible for conducting numerical and theoretical studies of turbulent flows and their associated geometric structures, focusing on passive and active scalar fronts, multiphase mixing layers, and
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the Research Group “ Numerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting September 1, 2025. The position is assigned to the research project "Randomization of Surrogates
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at the University of Sydney is currently seeking a Postdoctoral Research Associate (Physics) to work within the Dynamics and Neural Systems Group, led by A/Prof Ben Fulcher, on developing novel methods to analyze non