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classical topics in numerical analysis, such as the analysis of nonlinear PDEs or the development of new solver- or coupling-methods including their convergence analysis, but also modeling and simulation
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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(excavations and surface surveys), geophysical methods (including magnetometry), underwater research, as well as archaeometry (isotopic methods, bioarchaeology, histology). Numerous research projects
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— The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according
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skills 6. Competence in spoken and written English 7. Ability to work in a team Desirable criteria 1. Numerical skills, such as: Monte Carlo methods, Density Matrix Renormalisation Group
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of the fabricated fibers within optical networks. - Design of innovative hollow-core fiber structures using the finite element method. - Fabrication of specific optical fibers on a fiber drawing tower. - Linear
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orbital dynamics using analytic and numerical methods, (2) planet formation theory, (3) exoplanet architectures and demographics using statistical methods, and (4) planetary interior/atmosphere modeling
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English Ability to work in a team Desirable criteria Numerical skills, such as: Monte Carlo methods, Density Matrix Renormalisation Group or Truncated Conformal Space Approach Knowledge of quantum field
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(multiscale, QSP, PBPK, PK-PD).Apply numerical methods, optimization, and parameter estimation to calibrate models to experimental/clinical data.Perform sensitivity and uncertainty analyses to assess robustness
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 1 month ago
opportunity in computational inverse problems in the context of the ERC-StG European project Incorwave which aims to develop advanced numerical and mathematical strategies for passive imaging. This postdoctoral