Sort by
Refine Your Search
-
: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance
-
analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division, Computing and Computational
-
Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data
-
issues Preferred Qualifications: Experience supporting research computing, High Performance Computing, or large-scale data platforms Knowledge of distributed and high-performance file systems Experience
-
service offerings (e.g., large-scale geospatial compute pipelines, data ingest/curation/archive, analytics/visualization, user support). Establish operating policies, SLAs, user workflows, resource
-
Requisition Id 15817 Overview: We are seeking a Senior Procurement Officer who will provide senior level subcontract management support for a large construction project for a new data center. This
-
relationships between data and metadata. Collaborate on innovative solutions to automate and optimize the interplay between large scientific simulations, data ingestion, and AI processes (e.g., model training
-
Requisition Id 16004 Overview: The National Center for Computational Sciences (NCCS) at Oak Ridge National Lab (ORNL), which hosts several of the world’s most powerful computer systems, is seeking a
-
Requisition Id 16005 Overview: The National Center for Computational Sciences (NCCS) at Oak Ridge National Lab (ORNL), which hosts several of the world’s most powerful computer systems, is seeking a
-
Methods and Dynamics (MMD) Group at Oak Ridge National Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Methods for Data Reduction. Topics