Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
Laboratory (ORNL) invites outstanding candidates to apply for a staff position in the Data Analysis and Machine Learning Group. This group focuses on scientific computing with a strong emphasis on scientific
-
Requisition Id 15634 Overview: The Data Analytics and Machine Learning (DAML) Group is seeking an exceptional mathematician to work on the development of rigorous theory and algorithms needed
-
. Implement and optimize data representations and pipelines suitable for machine learning and uncertainty quantification. Collaborate with AI/ML experts to design and test inference methods that map
-
generators, protocol analyzer, and power analyzers. Experience with MicroTCA or AdvancedTCA platforms. Background in artificial intelligence (AI) and machine learning (ML) applications. Familiarity with
-
of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
-
, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible
-
topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and iterative solvers. Successful applications will work
-
-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency and reliability of scientific discovery
-
Ridge National Laboratory (ORNL) is seeking a staff fellow with expertise in machine learning and high performance computing to help develop high-fidelity computational tools that are used for large-scale
-
), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL, you will collaborate with a dynamic team of scientists and