Sort by
Refine Your Search
-
Earth scientists, geospatial experts, and computational scientists to leverage leadership-class computing resources for large-scale model training, testing, and deployment. Knowledge Dissemination
-
seeking to advance the separation science and technology for clean energy applications. Work with the Separation Technologies team to support a broad range of program development opportunities in the field
-
science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
-
visual representation and 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
-
at national scientific meetings Ensure compliance with environment, safety, health, and quality program requirements Take a position of leadership for day-to-day laboratory operations Participate in project
-
, industrial energy systems, energy efficiency of manufacturing industry, or other related fields. You will play a crucial role in the planning, execution, and optimization of our technical assistance program
-
, safety, health and quality program requirements Maintain strong dedication to the implementation and perpetuation of values and ethics Deliver ORNL’s mission by aligning behaviors, priorities, and
-
testing program. Security, Credentialing, and Eligibility Requirements: For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally
-
grid analytics, and scientific imaging. The successful candidate will design and implement sparse algorithms for large-scale scientific and numerical computations. This role offers an exceptional
-
, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science