Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 days ago
dynamics data and advanced graph-based deep learning models to decode long-range communication pathways within macromolecular complexes. The PhD candidate will play a central role in this effort by
-
Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 days 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
-
information, they are computationally intensive, which prevents their systematic use in large parametric studies. Consequently, simplified or surrogate models (e.g., 1D network models, reduced-order models
-
Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 22 days ago
the communication and storage needed to retain most of the information. Environment. The PhD will take place at Inria Grenoble, in the Thoth team. This is a large team focused on machine learning, and
-
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
-
the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
-
comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
-
Reflectometry The aim of the PhD project is to provide machine learning (ML) based neutron reflectometry (NR) analysis as an automatized workflow for the reflectometry instruments at the Institut Laue-Langevin