Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Nature Careers
- Aix-Marseille Université
- CEA
- Grenoble INP - Institute of Engineering
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- Université Grenoble Alpes
- IMT Mines Ales
- IRIT, Université de Toulouse
- Institut Pasteur
- Nantes Université
- Télécom Paris
- Université Claude Bernard Lyon 1
- Université de Bordeaux / University of Bordeaux
- Arts et Métiers Institute of Technology (ENSAM)
- CEA-Saclay
- FRANCE ENERGIES MARINES
- IMT - Atlantique
- IMT - Institut Mines-Télécom
- IMT Atlantique
- Institut des Hautes Etudes Scientifiques
- Institut des Hautes Études Scientifiques
- Institut of Mathematics of Marseille
- LE STUDIUM LOIRE VALLEY INSTITUTE FOR ADVANCED STUDIES
- Laboratoire National de Métrologie et d'Essais - LNE
- Mines Saint-Etienne
- NIMES UNIVERSITE
- Télécom SudParis
- Universite de Montpellier
- Université Marie et Louis Pasteur
- Université Savoie Mont Blanc
- Université Toulouse III Paul Sabatier
- Université de Caen Normandie
- Université de Lorraine
- Université de Toulouse
- université Strasbourg
- École nationale des ponts et chaussées
- 28 more »
- « less
-
Field
-
of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
-
resources to carry out your assignments. YOUR ASSIGNMENTS: The internship will develop and implement scalable, high‑performance algorithms for transient Lindblad dynamics tailored to the multi‑level Rydberg
-
recognitions and multi-class neural network algorithms. We propose to apply this emerging method to study samples from Europe, South Africa, and East Asia dated between 1.8 Ma and 60 thousand years ago (ka
-
. · Exploit the model(s) for design support and for the development of battery management algorithms. · Regularly exchange with industrial partners to co-develop and exploit models. · Monitor
-
opportunity to choose between two missions: • Mission 1: Improve new automated algorithmic schemes to quickly, efficiently and robustly detect and extract recorded geophysical signals related to earthquakes
-
automotive networks Explore and implement reinforcement learning algorithms for secure, real-time traffic scheduling and flow reconfiguration Conduct testbed-based evaluations using automotive-grade hardware
-
single needle, a robotic platform introduces complex motion control challenges that require the development of adaptive toolpath algorithm. This algorithm will ensure continuous and smooth deposition while
-
into refining computational strategies for large-scale molecular simulations in materials science and computational physics. The project will involve substantial numerical development, including algorithm design
-
training, as well as on machine learning or generative AI models. Technology watch on AI recommendation models and optimization of recommendation algorithms. Implementation of the recommendation engine
-
algorithms where the agent can propose updates to its own world model structure, but these updates are only accepted after a formal verification step confirms that the new model still adheres to its core