Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Nature Careers
- Ecole Centrale de Lyon
- Centrale Supelec
- CentraleSupélec Rennes campus
- European Synchrotron Radiation Facility
- IFP Energies nouvelles (IFPEN)
- INRIA
- Institut Pasteur
- Institut polytechnique UniLaSalle
- LEM3
- Nantes Université
- Universite de Montpellier
- Université Gustave Eiffel
- Université Toulouse Capitole
- Université côte d'azur
- cnrs
- 8 more »
- « less
-
Field
-
Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The Machine Learning for Integrative Genomics team (https
-
Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 19 days ago
leverage machine learning techniques to bypass IO bottlenecks in the context of physics simulation on high-performance computing (HPC) clusters. This work is thus placed in a broader ``Machine Learning for
-
differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 5 hours ago
Computer Science, Machine Learning, Bioinformatics, Computational Biology, or related fields. Strong experience in deep learning, ideally with PyTorch. Proven experience with graph neural networks, geometric deep
-
plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 5 hours ago
and fine-grained semantic information within the prompts, and assess geometric accuracy of corresponding models' answers. If necessary, we will then propose dedicated learning strategies for inducing
-
plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
-
users, thanks to the use of machine learning tools and techno-economic analyses. This project is aligned with the sustainable development goals (SDG) 7 and 10 of the United Nations, by promoting a low
-
or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
-
stochastic modeling, Bayesian inference, data fusion and modern machine learning. Its research activities span various application domains such as security, non-destructive testing, infrared imaging and