Sort by
Refine Your Search
-
Listed
-
Employer
- CNRS
- Ecole Normale Supérieure de Lyon
- Inria, the French national research institute for the digital sciences
- Télécom Paris
- CEA-Saclay
- IFP Energies nouvelles (IFPEN)
- IMT MINES ALES
- IMT Mines Ales
- INSTITUT MAX VON LAUE - PAUL LANGEVIN
- Institut Pasteur
- Universite de Montpellier
- Université Grenoble Alpes
- École nationale des ponts et chaussées
- 3 more »
- « less
-
Field
-
Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. For more information about AMBER, visit: https
-
Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
the machine learning community as challenging, high-dimensional testbeds. Notably, the recently developed WOFOSTGym simulator \cite{solow2025wofostgym}, bridging crop modeling and RL, received the Outstanding
-
Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 2 months ago
hyperscanning neuroimaging data, using advanced statistics and machine learning methodologies for temporally-sensitive data, such as GLMM, Random Forests, LSTM, etc.. Use of MatLab for pre-processing, and
-
computer scientist with experience in bioinformatics, solid programming skills and knowledge in 3D protein structures. Machine learning skills and knowledge of Web development are a plus. Good interpersonal
-
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
-
Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
-
on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify
-
of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for