Sort by
Refine Your Search
-
Listed
-
Employer
- CNRS
- Nature Careers
- IMT Atlantique
- CEA
- IFREMER - Institut Français de Recherche pour l'Exploitation de la MER
- IMT - Institut Mines-Télécom
- ONERA
- Université Grenoble Alpes
- Université de Lille
- Université de Limoges
- CNRS - Observatoire de Paris-Meudon
- Centre de Mise en Forme des Matériaux (CEMEF)
- Clermont Auvergne INP
- Computer science laboratory of Le Mans Université (LIUM)
- Ecole Centrale de Lyon
- FEMTO-ST institute
- INSA Strasbourg
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Mines Paris-PSL
- Observatoire de Paris
- Télécom SudParis
- UNIVERSITE ANGERS
- UNIVERSITE D'ORLEANS
- Université Angers
- Université Paris-Saclay GS Physique
- Université d'Orléans
- Université de Bordeaux
- Université de Haute-Alsace
- Université de Montpellier
- Université de Savoie Mont-Blanc
- Université de Toulouse
- fluiidd
- 23 more »
- « less
-
Field
-
cylinder flow. Journal of Fluid Mechanics, 896, A24. Your research program After getting familiar with the existing mathematical formalism and numerical tools, you will develop new algorithms to efficiently
-
techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
-
of market-making algorithms (for threshold selection, and finding the optimal size of windows/batches)
-
Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
of this project requires the design, development, and training of an artificial intelligence algorithm capable of automatically segmenting the bony structures of both healthy and fractured tibial plateaus
-
the technical side, we aim at combining statistical latent variable models with deep learning algorithms to justify existing results and allow a better understanding of their performances and their limitations
-
research work will be to devise efficient algorithms for source separation in DAS measurements. Issues such as large data volumes that can exceed 1 To per day and per fiber, instrument noise, complex nature