Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
-
health research projects. The research activities include HIPAA compliant research data that has been entrusted to ORNL by sponsors such as the National Cancer Institute. We work on some of the most
-
bottlenecks, and develop strategies for improving computational efficiency. Work effectively individually and within a team to engineer large multi-component scientific and data-intensive software to meet the
-
materials. In this role, you will develop and apply methods that integrate physics‑guided image correction with intelligent (AI/ML‑enabled) data‑acquisition strategies. Key objectives include (1) implementing
-
and clustered computing services to researchers who process large data sets and/or develop code as a part of their project. Ensure the availability, performance, scalability, and security of production
-
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
-
, supported by: Multiscale modeling (material (molecular) → process → manufacturing (scale up)) Data-informed experimentation Selective use of AI/ML and big-data techniques where they add real value
-
service offerings (e.g., large-scale geospatial compute pipelines, data ingest/curation/archive, analytics/visualization, user support). Establish operating policies, SLAs, user workflows, resource
-
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