La Sismicité Des Zones Continentales Stables - Paris, France - Ecole normale supérieure

Ecole normale supérieure

Entreprise vérifiée

Paris, France

il y a 3 semaines

Posté par:

Sophie Dupont

beBee Recruiter

Description

**La sismicité des zones continentales stables // Micro
- and moderate seismicity in Stable Continental Regions**:

Réf
ABG-121817

ADUM-55634

Sujet de Thèse 26/03/2024
Ecole normale supérieure
Lieu de travail
Paris
France
Intitulé du sujet
La sismicité des zones continentales stables // Micro

- and moderate seismicity in Stable Continental Regions

Mots clés
Sismologie, Deep learning
Seismology, Deep learning
Description du sujet:
[-]

In the frame of the iQuake project, funded by the ERC , we seek to hire a PhD student for a duration of three year.

The project involves building new catalogs of low-magnitude seismicity (microseismicity) in stable continental regions using recent machine-learning-based earthquake detection techniques.

The catalogs will be used to constrain new models of the rheology of marginally deformed continental regions. The PhD student will join the team of Pr.

Romain Jolivet at Ecole normale supérieure - PSL in Paris, France and work within the Laboratoire de Géologie de l'ENS hosted by the Département de Géosciences.

While most earthquakes occur along rapidly deforming plate boundaries, continental interiors are less often struck by devastating earthquakes. Over the last centuries, multiple events have left scientists puzzled as to how could such earthquake occur as they do not follow the classic and now quite well accepted description of earthquakes as the response of a frictional interface to stress which more or less constantly increases with time. In continental interiors, no relative motion is observed across the faults responsible for those earthquakes, which by themselves indicate that elastic strain energy is available in the upper crust. In the iQuake project, we seek to explore the distribution of seismicity within such Stable Continental Regions using Machine Learning technologies on seismic and geodetic data (WP1) and uncover the various stress perturbations acting on the continents at all temporal and spatial scales (WP2) to test an elastoplastic rheology implementing static fatigue (WP3). The project will start in Septembre 2024.

Début de la thèse : 01/10/2024
Nature du financement:

Précisions sur le financement:

Programmes de l'Union Européenne de financement de la recherche (ERC, ERASMUS)
Présentation établissement et labo d'accueil:
Ecole normale supérieure
Etablissement délivrant le doctorat:
Ecole normale supérieure

Ecole doctorale:

398 Géosciences, Ressources Naturelles et Environnement Formation solide en sciences de la Terre ou en traitement du signal. Connaissances en intelligence artificielle. Connaissances en code (python ou c++).
Solid background in earth sciences or in signal processing. Skills in artificial intelligence. Skills in python. 17/05/2024