Sort by
Refine Your Search
-
, and cyber-resilient operation of distribution systems and networked microgrids. The successful candidate will contribute primarily to the control and cybersecurity thrusts of a multi-institutional
-
The Industrial Technologies Group within the Energy Systems and Infrastructure Assessment (ESIA) Division at Argonne National Laboratory seeks a highly qualified Postdoctoral Appointee to conduct
-
The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in physics of colloidal systems. The postdoc is expected to conduct research
-
energy goals. ESIA also develops, deploy, and advance grid technologies that ensure a robust and secure U.S. grid transmission and distribution system. We collaborate with government agencies as
-
, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
-
phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in reactive systems Use modeling tools such as computational fluid dynamics
-
The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
-
measurement Experience in x-ray diffraction techniques Experience designing and building experimental control and data acquisition systems Ability to model Argonne’s core values of impact, safety, respect
-
The Multiphysics Computations Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing high-fidelity scale-resolving computational fluid dynamics (CFD
-
for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems. The postdoc will work on multimodal data