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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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candidate will work on cutting-edge research integrating genome-scale language models (GenSLMs) with deep mutational scanning data, and experimental virology to predict viral evolution and identify emerging
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-be-completed PhD (typically completed within the last 0-5 years) in chemistry, chemical engineering, material science, or related fields. Demonstrated knowledge in materials synthesis and
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Leadership Computing Facility (ALCF), the Mathematics and Computer Science Division (MCS), the Computational Science Division (CPS), and the Data Science and Learning Division (DSL). The postdoctoral
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The Advanced Grid Modeling group at Argonne National Laboratory's Center for Energy, Environmental, and Economic Systems Analysis is seeking a dedicated Postdoctoral Researcher. This role is ideal
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and methods, fostering innovation and accelerating progress in the development of efficient solar energy conversion technologies. Position Requirements Recent or soon-to-be-completed PhD (within
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to solve challenging problems in the microelectronics area. Note: Synthesis of bulk materials, first-principles simulations/modeling, and organic or bio-related areas are not in consideration
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Energy Systems and Infrastructure Analysis Division. We are seeking applicants with a strong technical background and expertise in international trade modeling, particularly in the upstream automotive
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vacuum instrumentation. U.S. citizenship is required for this position. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. The position is initially for one (1