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(CO2) conversion processes and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will contribute
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conducted by developing intelligent systems that can function as collaborative partners in the scientific process. Our group is pioneering the development of (1) generative AI models and agentic architectures
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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fluorometric profiles of cyanobacteria using devices such as the Beckman Coulter Cytoflex Bioinformatics – Basic scripting experience in languages such as Python, R or BASH to carry out rudimentary genomics
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to develop and
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undergraduate students. Postdocs can benefit from strong collaborations with applied mathematicians, computer scientists, device physicists, materials scientists, and statisticians; they will also have access
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highly competitive salary and a generous professional allowance to support travel, collaborations, and career development. For additional details, including a list of past recipients, see https
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closely with senior members of the research group. The term of the positions is typically two years, with the possibility to renew for the 3rd year, contingent on the project process and availability
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interests Three letters of reference More details on the CPAC group can be found on our website: https://cpac.hep.anl.gov Completed applications will be reviewed as received, with all applications submitted
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. The successful candidate should have expertise and experience in process modeling, techno-economic analysis (TEA) and life cycle analysis (LCA) of lithium-ion batteries and/or recycling and resources to products