65 application-forms "https:" "https:" "https:" "UCL" research jobs at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
, Credentialing, and Eligibility Requirements: For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department
-
. Background in semiconductor sensor physics or microelectronics. Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements
-
environment, set priorities, multi- task and adapt to ever changing needs Security, Credentialing, and Eligibility Requirements For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form
-
participate creatively in a collaborative, team environment. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree
-
Requisition Id 15656 Overview: The Geochemistry and Interfacial Sciences Group in the Chemical Sciences Division (CSD) at Oak Ridge National Laboratory (ORNL) invites outstanding applications for a
-
Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. The applicant will also work closely with scientists at CNMS as well as those involved in a multi-institution collaboration (~30 researchers) spanning Oak Ridge National Laboratory, Argonne National Laboratory
-
Requisition Id 15421 Overview: The Multiscale Methods and Dynamics (MMD) Group at Oak Ridge National Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related
-
to work independently and to participate creatively in collaborative teams across the laboratory. Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
-
for the manufacturing of next generation materials for different potential market applications to evaluate the life cycle economic, energy, and environmental impacts. The focus of these analyses is to understand
-
computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and