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The Multi-Physics Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee on the topic of CFD modeling of internal combustion engines fueled by low-carbon fuels
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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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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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
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We are seeking a Postdoctoral Appointee to work in the Mathematics and Computer Science (MCS) Division of the Computing, Environment, and Life Sciences directorate (CELS) of Argonne National
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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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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
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research groups. Skills for effective communications, verbally and through writing. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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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