Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
for Artificial Intelligence. https://miai.univ-grenoble-alpes.fr/ Activities Develop and evaluate deep learning tools for MRI fingerprint data Write scientific articles Present results at international conferences
-
from renewable electricity and sustainable raw materials, represent a promising solution, enabling deep decarbonization. DESIRE is a Marie Sklodowska-Curie doctoral network that aims to train 15 doctoral
-
research group in computer vision and machine learning, with seminal results in 3D reconstruction from images, scene understanding, deep learning, optimization, sparsity, etc. IMAGINE is part of
-
frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data
-
prioritization. By explicitly combining ecology, economics, and decision theory, EcoDisco seeks to produce methods that are robust, policy-relevant, and sensitive to the deep uncertainties inherent in conservation
-
-informed deep learning is rapidly advancing, integrating artificial intelligence with the governing physical laws to achieve more faithful representations of atmospheric processes. In the field of remote
-
) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
-
, data-driven algorithms, deep reinforcement learning The Pprime laboratory is a CNRS Research Unit. Its scientific activity covers a wide spectrum from materials physics to mechanical engineering
-
influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and
-
for automatic process generation. Generative approaches, using deep learning algorithms, can generate new process structures, surpassing conventional optimization techniques. Objectives of the ATHENA project