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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
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. Integrate domain knowledge from power systems with modern ML methods to create physics-informed, interpretable, and operationally relevant solutions. Build and evaluate models using realistic utility or test
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We are seeking creative Postdoctoral researchers to bridge the gap between leadership-class supercomputing and cutting-edge open science in the area of AI and Machine Learning. Successful candidates
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studies and port these simulations to leadership class supercomputing platforms, identify and improve the bottlenecks in scaling the simulations. Analyze large simulation datasets to gain new scientific
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devices, with emphasis on lithium-ion, sodium-ion, and lead-acid battery systems. Modeling and analysis will leverage tools such as COMSOL, MATLAB, Excel, Python, and related scientific software. The role
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synchrotrons and x-ray free-electron lasers. Key Responsibilities Perform electronic-structure calculations using ab initio quantum chemistry methods and software (commonly CASSCF-based approaches) Investigate a
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, and use of novel architectural features. Argonne National Laboratory is a multi-disciplinary research institution offering world-class opportunities in High-Performance Computing and housing the Argonne
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of the upgraded APS, leadership-class computing at the Argonne Leadership Computing Facility (ALCF), and state-of-the-art microscopy at the Center for Nanoscale Materials (CNM). Candidates with a strong background
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materials from complex feedstocks to achieve the desired product quality and form. As a part of this team, you will: Apply electrochemical engineering principles to develop processes such as oxide reduction
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needs. As a part of this team, you will : Develop, build and test equipment and perform molten salt separations which support the development of a secure fuel supply for MSRs and nuclear fuel cycle