Sort by
Refine Your Search
-
Listed
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Aix-Marseille Université
- Nantes Université
- Universite de Montpellier
- Université Claude Bernard Lyon 1
- Aix-Marseille University
- CEA-Saclay
- FRANCE ENERGIES MARINES
- French National Research Institute for Sustainable Development
- IMT - Atlantique
- IMT Mines Albi
- INSA Strasbourg
- Institut Pasteur
- Institut of Mathematics of Marseille
- Nature Careers
- Observatoire de la Côte d'Azur
- Université Grenoble Alpes
- l'institut du thorax, INSERM, CNRS, Nantes Université
- 9 more »
- « less
-
Field
-
project combines techniques from machine learning, natural language processing (NLP), and knowledge representation to support legal scholarship and decision-making. The position entails close academic
-
: In decreasing priority order, experience in: • Model fitting and/or image reconstruction in astrophysics • Active Galactic Nuclei • Machine learning • Optical long baseline interferometry and data
-
perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
-
machine learning tools. The postdoctoral fellow will contribute to various aspects of the project, such as: * developing new theoretical and numerical approaches for determining the thermodynamic and
-
in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in
-
, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
-
a team More specifically: - For mission 1: knowledge of signal and image processing, machine learning (PyTorch or TensorFlow + NumPy/SciPy), statistical processing & data and results visualisation
-
skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
. At the microscale, grain interactions—governed by nonsmooth phenomena, e.g. contacts, friction—drive the bulk dynamics at the macroscale, which challenge current modelling frameworks. Modern experimental methods
-
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