-
-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference
-
clustering, redshift-space distortions, weak/strong gravitational lensing, and artificial intelligence/machine learning (AI/ML). The observational focus is on optical sky surveys (DES, DESI, Roman, Rubin Obs
-
, 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
-
(HPC). The postdoc will work closely with visualization researchers, AI scientists, and domain application teams across Argonne and the broader DOE ecosystem. The goal of this postdoctoral position is to
-
computational research. They are intrinsically driven, goal-oriented, and can work collaboratively with others. Working closely with the CPS divison, the postdoc will leverage AMReX and the LBM to develop
-
) of electrochemical energy storage devices (diagnosis) and predict the SOH into the future (prognosis). The primary projects this postdoc will contribute to relate to lithium-ion batteries, advanced lead-acid batteries