Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
Additional Information Eligibility criteria Transversal knowledge required : - Expertise in machine learning and deep learning in particular - Knowledge in ecology, marine biology, or oceanography would be a
-
) About the Project Deep learning models, and in particular large language models (LLMs), have demonstrated remarkable capabilities but remain limited by their heavy computational requirements, lack
-
Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 17 days ago
with expertise in medical image processing—particularly registration and segmentation—and proven experience in deep learning, with a focus on ultrasound imaging. Prostate cancer diagnosis relies
-
Processing Skills required: - Medical computer programming: python, 3D slicer, LCmodel (optional), FSL, spm, ants) - Artificial Intelligence skills and deep learning experience - Proficiency in Tensorflow
-
, robustness under varying turbulence, and autonomy for distributed systems. To address this, the group integrates Artificial Intelligence into AO control loops, using deep learning to handle sensor
-
to improve our understanding of the formation and evolution of oceanic crust. Samples from several drilled and dredged areas are available in the CRPG collection (EPR: Hess Deep, MAR: Atlantis Massif, SWIR
-
associated with phenotypic (biomechanical and metabolomics) traits. Estimate locus-specific effect sizes and quantifying genetically-driven phenotypic variations. Develop Bayesian models and/or deep learning
-
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
-
dimensional information, classification and/or deep learning methods may also be developed. In addition, the complementarity between the different data sources used (particularly between aerial LiDAR data and
-
from one round to the next, and eventually the library collapses to a few selected functional aptamers. The evolution can be tracked in detail by deep sequencing of the successive rounds. The goal