Sort by
Refine Your Search
-
be to develop high fidelity simulations and/or algorithms to enable Bragg coherent diDraction imaging. We expect x-ray ptychography and coded aperture methods to play a fundamental role in creating a
-
for projects related to the integration of microgrids, distributed energy resources (DERs), and advanced transmission & distribution (T&D) coordination. This role is ideal for a researcher passionate about
-
heterointegration with other materials for developing energy efficient devices. The postdoctoral candidate will be a part of highly collaborative research team focusing on the synthesis and characterization aspect of
-
for a predoctoral/postdoctoral researcher position in research data management. Position Overview The candidate will manage and coordinate data activities across ESRA. You will work closely with
-
that are broadly applicable across the physical sciences but applied initially to x-ray characterization needs. They will publish results in high impact journals, present at conferences and work with the software
-
The Applied Materials Division (AMD) at Argonne National Laboratory is seeking to hire a Post-doctoral Researcher. The candidate will work within a multidisciplinary team with researchers
-
, primarily for recycling used nuclear fuel for use in advanced reactors. As a part of this team, you will: Apply electrochemical engineering principles to develop processes such as metal oxide reduction and
-
. Although exceptional candidates in all areas of experimental condensed matter and materials physics will be considered, particular emphasis will be placed on expertise in materials and phenomena towards use
-
will conduct Research and Development to help develop processes for the economic production of critical and rare earth metals. Perform technical work related to the development of new processes
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate