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UID:submissions.supercomputing.org_SC23_sess503_job217@linklings.com
SUMMARY:Postdoctoral Appointee for Applied AI in Electrochemical Device Di
 agnosis & Prognosis
DESCRIPTION:We are currently seeking a Postdoctoral candidate to join our 
 team in the Data Science and Learning division at Argonne. This is an oppo
 rtunity for a knowledgeable and creative individual to be part of a team u
 sing artificial intelligence (AI) and high-performance computing (HPC) to 
 evaluate the state of health (SOH) of electrochemical energy storage devic
 es (diagnosis) and predict the SOH into the future (prognosis). \n\nThe pr
 imary projects this postdoc will contribute to relate to lithium-ion batte
 ries, advanced lead-acid batteries, and flow cells with applications inclu
 ding long duration energy storage and electrified aviation. Each project w
 ill involve close collaboration with domain experts to leverage emerging c
 omputing techniques to solve pressing challenges in energy storage. \n\nPr
 imary responsibilities will be to design and implement new techniques for 
 the diagnosis and prognosis of electrochemical energy storage systems. Whi
 le experience in electrochemical modeling is a benefit, ideal candidates w
 ill be expected to work together with domain experts rather than possess a
 ll required expertise themselves. Beyond the listed projects, the candidat
 e will be able to contribute to other large-team scientific projects in ma
 terials engineering, chemistry, and beyond at Argonne National Laboratory.
 \n\n
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