58 data-"https:" "https:" "Université de Toulouse LGC" Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement
-
to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
-
science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
-
in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
-
production and neutron irradiation. To learn more about Neutron Sciences at ORNL, please go to this link: http://neutrons.ornl.gov The Postdoctoral Research Associate will focus on scientific projects
-
on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems
-
related experimental data. This position resides in the Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL) and is embedded in the MAIQMag (Multimodal AI
-
, United States of America [map ] Appl Deadline: (posted 2025/10/03, listed until 2026/04/03) Position Description: Apply Position Description Overview: The Data and AI Systems Research Section/Workflow Systems Group within
-
capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data
-
Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and analysis of large-scale 2D/3D scientific data