Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- CNRS-ENS-UCBL
- Institut Pasteur
- Universite de Montpellier
- Université Paris-Saclay GS Physique
- Université Savoie Mont Blanc
- Université de Caen Normandie
- Université de Technologie de Belfort-Montbéliard
- École nationale des ponts et chaussées
-
Field
-
Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 27 days ago
., & Sen, M. K. (2007). Grid dispersion and stability criteria of some common finite‐element methods for acoustic and elastic wave equations. Geophysics. Chaljub, E., et al. (2007). Spectral element analysis
-
Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 2 months ago
coupling with adaptive meshes. High-order spectral finite element methods (SFEM) offer superior accuracy per degree of freedom and are naturally suited to HPC architectures (CPU/GPU clusters). Two main
-
Eligibility criteria Numerical analysis and finite element method Solving anisotropic problems Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7340-SOPBAU-024/Default.aspx Work Location
-
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
-
differences, finite volumes, finite elements, spectral methods) - At least one experience in developing a numerical solver for a differential equation or in developing a diagnostic for a numerical simulation
-
The successful candidate will hold a PhD in applied mathematics, and will have knowledge of PDE discretization methods such as finite elements, finite volumes, etc. Practical knowledge of at least one programming
-
finite elements, finite volumes, etc. Practical knowledge of at least one programming language (preferably C++). English : level C2 _ All research exchanges will be in English Additional comments ERC
-
engineering, finite element modelling • Probability theory, stochastic process modelling, statistical tools • Artificial Intelligence and Machine learning approaches • Programming (python) A first experience
-
candidate has experience in coding numerical solutions to partial differential equations via the finite element method / finite differences schemes and programming skills in Mathematica, Matlab, Python
-
knowledge of numerical methods - knowledge of free-surface flows, granular flows - proven experience in numerical simulation (finite elements, finite volumes, CFD, LES, etc.) - proficiency in basic scientific