56 structural-engineering-"https:"-"Simons-Foundation" Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
Design Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). This position lives in the Alloy Behavior and Design Group
-
through the High Flux Isotope Reactor, the Radiochemical Engineering Development Center, ORNL's other nuclear facilities, and an assemblage of world-leading scientists and engineers. Please visit https
-
to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
-
properties of the above materials. Collaborate with ORNL postdocs and staff who are involved in structural characterization. Participate in the development of new ideas and projects. Present and report
-
challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
-
engineers, leveraging cutting-edge resources; most notably the Frontier supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research
-
Requisition Id 15408 Overview: Oak Ridge National Laboratory (ORNL) (https://www.ornl.gov/) is the largest US Department of Energy science and energy laboratory, conducting basic and applied
-
states, magnetic phase transitions, and corresponding structural responses at high magnetic fields, using high flux neutron scattering techniques. Additionally, collaborative work will be performed with
-
management skills are required. This position resides in the Deposition Science and Technology Group at the Manufacturing Demonstration Facility (MDF) in the Manufacturing Sciences Division (MSD), Energy
-
scientists, engineers, and facility operators to integrate AI seamlessly into experimental and computational pipelines. Demonstrate the effectiveness of dynamic workflows in representative use cases such as