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Field
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synaptic resilience and the reliability of synaptic responses. The work primarily involves mathematical modeling and numerical simulation, but also the analysis of experimental datasets for model validation
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Experience with: Structured population models, Multiscale modelling, Numerical analysis of PDEs, Machine learning for parameter inference, Model calibration and sensitivity analysis. Familiarity with systems
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] (AI-assisted Simulations of Microstructure driven MEchanical properties from high Throughput and multiscale analysIS), in the framework of PEPR DIADEM[2] , which aims to develop an advanced
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AMMETIS[1] (AI-assisted Simulations of Microstructure driven MEchanical properties from high Throughput and multiscale analysIS), in the framework of PEPR DIADEM[2] , which aims to develop an advanced
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carbon cycling, with a focus on boreal forest ecosystems Experience with data processing software for eddy-covariance data (EddyPro, REddyProc) Excellent numeric and analytical problem-solving skills
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part of this project, the thesis will focus, on the one hand, on a detailed analysis of gas phase inhibition kinetics by combining experimental and numerical studies to determine global parameters (auto
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two main parts: • numerical modeling of crustal stresses associated with the various proposed mechanisms; • statistical analysis of the impact of these stresses on faults, potentially active or not, and
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in the presence of imperfections introduced by the laser and/or intensity and phase modulators. Perform a finite-key analysis of the security of these. systems in the presence of such imperfections
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properties of individual materials depending on the temperature. The results obtained from the numerical analyses give a relatively objective picture of the behavior of materials under the influence
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interface of hydrology and geophysics, to gain extensive experience in field experiments, data analysis, numerical modeling, and scientific programming, and to contribute to fundamental advances in