Sort by
Refine Your Search
- 
                Listed
- 
                Employer- CNRS
- Inria, the French national research institute for the digital sciences
- Aix-Marseille Université
- Télécom Paris
- Université Claude Bernard Lyon 1
- Université Grenoble Alpes
- Université Savoie Mont Blanc
- Ecole Centrale de Lyon
- Ecole Normale Supérieure de Lyon
- FRANCE ENERGIES MARINES
- IMT - Atlantique
- Institut of Mathematics of Marseille
- Nantes Université
- Télécom SudParis
- Universite de Montpellier
- Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO
- Université Toulouse III Paul Sabatier
- Université de Bordeaux / University of Bordeaux
- École Normale Supéireure
- 9 more »
- « less
 
- 
                Field
- 
                
                
                (MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop 
- 
                
                
                Is the Job related to staff position within a Research Infrastructure? No Offer Description The researcher will use and further develop ptychography algorithms for transmission electron microscopy data 
- 
                
                
                by the CNRS, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical 
- 
                
                
                ) for the high-luminosity phase of the LHC, in particular on its mechanical design, on the generation of the L1 trigger primitives, and on the development of offline reconstruction algorithms. In addition, it is 
- 
                
                
                pressure sensors, allowing them to measure the movements of the fish and detect pressure signatures in their wake. Numerical simulations were developed to predict the hydrodynamic signatures generated by 
- 
                
                
                • Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute 
- 
                
                
                on the development of deep learning methods for reconstruction and physics analysis of the ATLAS experiment data. The successful candidate will develop innovative analysis methods for the reconstruction or the physics 
- 
                
                
                . However, conventional neural networks are not well-suited to the computational constraints of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted computations 
- 
                
                
                Paris, is one of France's top engineering schools. The mission of the school is to educate, imagine, and design digital technologies for a society that respects people and their environment. We 
- 
                
                
                candidate will lead the solution of these open problems through the development and implementation of RL algorithms. They will have the opportunity to make a significant impact in the field of trustworthy and