Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Nature Careers
- CNRS
- Institut Pasteur
- CEA
- École nationale des ponts et chaussées
- Géoazur laboratory
- IFP Energies nouvelles (IFPEN)
- IMT MINES ALES
- Inria, the French national research institute for the digital sciences
- Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO
- Université d'Artois
- Université de Montpellier
- 2 more »
- « less
-
Field
-
exploration strategies that go beyond traditional techniques such as linear programming or deterministic solvers. You will work on cutting-edge methods including: Bayesian optimization Surrogate modeling
-
Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 4 days ago
induces reduced footprints for processors and less space for the battery. On the audio processing latency front (iii), DNN inference is notoriously slower for real-time audio DSP than “traditional” methods
-
the solution of the inner problem. In recent years, efficient techniques for bilevel optimization have emerged, leveraging automatic differentiation and stochastic approximations. However, these methods often
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
Leveraging the spatio-temporal coherence of distributed fiber optic sensing data with Machine Learning methods on Riemannian manifolds Apply by sending an email directly to the supervisor
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
. Processing this response provides estimates of the local variations in acoustic pressure along the fiber, over distances ranging from 40km up to 140km with some systems. This technique, called Distributed
-
or microtubules. On the other hand, we have designed physics-inspired data-driven methods aiming at estimating suitable prior regularization models via Plug&Play denoisers [SMCBF23] and/or Wasserstein GANs as
-
domain-independence with the goal of incrementally moving from a specific chemistry knowledge graph dedicated prototype to a domain-independent solution. Design a generic and declarative method for tool