67 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" research jobs in France
Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Universite de Montpellier
- Ecole Normale Supérieure de Lyon
- Institut Pasteur
- Université de Bordeaux / University of Bordeaux
- CEA-Saclay
- Fondation Nationale des Sciences Politiques
- Grenoble INP - Institute of Engineering
- IFP Energies nouvelles (IFPEN)
- IMT MINES ALES
- IMT Mines Albi
- IMT Mines Ales
- INSA Strasbourg
- Nantes Université
- Nature Careers
- Télécom Paris
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- University of Strasbourg
- Université Grenoble Alpes
- Université Savoie Mont Blanc
- l'institut du thorax, INSERM, CNRS, Nantes Université
- École nationale des ponts et chaussées
- 13 more »
- « less
-
Field
-
, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
-
the creation of high-precision digital twins. Activity 1: Integration of Photometric Stereo in Meshroom - Implement processing nodes for normal field and intrinsic color estimation. - Integrate deep learning
-
University of Savoie Mont Blanc (USMB) that brings together expertise in machine learning and information fusion, as well as networks and systems. It develops methods for processing and managing data in
-
silico identification of candidate developmental pathways explaining tradeoff variation. Contribute to advanced statistical analyses and interpretable machine learning approaches (in collaboration with
-
, France [map ] Subject Areas: Machine Learning / Machine Learning Statistics Statistical Physics Mathematics Probability Appl Deadline: 2025/12/20 11:59PM (posted 2025/11/25, listed until 2026/05/25
-
, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
-
self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
-
active materials by making use of artificial molecular machines. SPRING will establish innovative concepts to elaborate (i) active (supra)molecular systems, (ii) new synthetic objects to study some
-
researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
-
Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a