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analysis and Multiphysics Computational modeling of metal alloys using an Integrated Computational Materials Engineering (ICME) approach. Responsibilities: 60% Perform research on the microstructural
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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and outstanding education are interlinked and equally valued. We are seeking to appoint a Postdoctoral Researcher in Computational Materials Modelling to join the Multiscale Materials Modelling Group in
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, and can analogous mechanisms be engineered into multi-agent AI systems? You would answer this question by building and testing computational models, developing multi-agent simulations where agents
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Zanna, the successful candidate will focus on developing generative machine learning models for complex dynamical systems for probabilistic forecasts. The postdoc will be expected to lead independent
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Argonne National Laboratory is seeking a highly skilled Postdoctoral Researcher to work in the Separations and Bioprocessing Group in the Applied Materials Division (AMD) on developing, designing
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channels modulates these pathways. We use mouse models and primary human cells to query immune function in vitro and in vivo. Core experimental techniques include mouse disease models, in vitro functional
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remote sensing approaches using ocean-color and thermal-infrared satellite observations to study marine organosulfur compounds and ocean–atmosphere interactions. Key research activities include algorithm
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learning, memory, and/or decision-making - Experience and/or interest in conducting developmental research - Experience with computational modeling approaches - Experience acquiring, analyzing, and
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and