79 phd-position-in-source-function "AAAS" Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, computer science, or a related field completed within
-
Excellent written and oral communication skills Ability to work independently and to participate creatively in collaborative teams Ability to function in a fast-paced research environment, set priorities
-
are subject to performance and availability of funding. Special Requirements: HSPD-12 PIV badge: This position requires the ability to obtain and maintain an HSPD-12 PIV badge. About ORNL: As a U.S. Department
-
land loss and vegetation change at high spatial resolution Work closely with remote-sensing scientists, modelers, and empiricists across DOE laboratories and universities to address project objectives
-
development in areas such as reactor core physics, nuclear fuel cycle assessments, radionuclide inventories, and source terms. The major customers of the work performed in this group are the National Nuclear
-
Requisition Id 16949 Overview: We are seeking a Postdoctoral Research Associate who will focus on efforts related to gas dynamics, fluid flow, and mass transfer. This position resides in the Applied
-
(NSSD). In this role, you will conduct fundamental research into the integration of Bayesian methodologies with system dynamics modeling, advancing statistical methods and the open-source scientific
-
. Preparation of composite, ceramic, and alloy samples for testing and performance assessment will be a routine function. Rad Worker training will be offered for working with irradiated materials. This position
-
opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in chemical engineering, chemistry, mechanical engineering, civil
-
. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from the SPRUCE (Spruce and