Sort by
Refine Your Search
-
Listed
-
Employer
- CNRS
- Aix-Marseille Université
- Ecole Centrale de Lyon
- Nantes Université
- CEA
- Consortium Virome@tlas
- FRANCE ENERGIES MARINES
- French National Research Institute for Sustainable Development
- INSTITUT NATIONAL DES SCIENCES APPLIQUEES
- Inria, the French national research institute for the digital sciences
- Institut of Mathematics of Marseille
- Laboratoire d'Astrophysique de Marseille
- Observatoire de la Côte d'Azur
- Télécom SudParis
- Université Grenoble Alpes
- Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO
- Université Savoie Mont Blanc
- École Normale Supéireure
- 8 more »
- « less
-
Field
-
dozen input variables). The foreseen approach would be to build on recent developments in using CNNs for Species Distribution Models (e.g. Deneu et al 2021, Morand et al 2024) to summarise the complex
-
to contribute to the development of fundamental aspects of computer science (models, languages, methods, algorithms) and to develop synergy between the conceptual, technological and societal challenges associated
-
the nature of the ambient noise in the reactor (spectrum, spatial and temporal distributions, levels), the approach consists in developing passive methods by determining their conditions of use but not
-
5 Sep 2025 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Computer science Mathematics » Algorithms
-
tomography (SPECT) is an imaging technique that tracks the 3D distribution of a radioactive tracer administered to a patient to monitor certain biological functions. The long acquisition times (10-40 minutes
-
control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
-
Navier-Stokes equations at a macroscopic level, the LB method considers the fluid at a kinetic level. Capturing the dynamics of collections of fluid particles distributed over a lattice is here preferred
-
analysis, as many observed phenomena cannot be adequately modeled by stationary processes. The NOMOS project aims to develop a new generation of nonstationary models and algorithms for analyzing various
-
nonstationary models and algorithms for analyzing various biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential
-
the necessary data from numerical models and observations to build the dataset; Identify the algorithms best suited to learn the targeted behaviors; Train the learning models; Validate their ability to predict