Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Nature Careers
- CNRS
- Institut Pasteur
- CEA
- Inria, the French national research institute for the digital sciences
- The American University of Paris
- Université de Technologie de Belfort-Montbéliard
- American University of Paris;
- Arts et Métiers Institute of Technology (ENSAM)
- BRGM
- CEA-Saclay
- Ecole Centrale de Lyon
- FEMTO-ST institute
- IMT MINES ALES
- UNIVERSITE PARIS CITE
- Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO
- Université Paris-Saclay GS Mathématiques
- Université Savoie Mont Blanc
- Université d'Artois
- Université de Montpellier
- École Normale Supéireure
- École Normale Supérieure
- École nationale des ponts et chaussées
- 13 more »
- « less
-
Field
-
research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
-
unit (UMR 7248) from UCA and CNRS. Abstract Optical flow estimation is a key task in computer vision, particularly critical for autonomous navigation where accurate motion perception is essential. It can
-
of and experience with hydrological and/or hydrogeological modeling - Knowledge of and experience with AI concepts (machine learning, deep learning, and PINNS) and/or digital twin development - Experience
-
Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
. This dataset will enable the training of specialized deep learning models (neural network or transformer) for automated segmentation of tibial plateau fractures. iii) The algorithm must then be trained
-
, engineering, bioinformatics, machine learning, artificial intelligence) to support minimally invasive and targeted preventive and predictive medicine capable of limiting age-related functional disorders
-
by exploiting foundational machine-learning potentials such as MACE, SevenNet, or Orb-V3. The predictions will then be progressively refined and verified by DFT and, ultimately, tested experimentally
-
correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
-
interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
-
experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
-
particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and