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The Buildings & Industry Group within the Energy Systems and Infrastructure Analysis (ESIA) Division at Argonne is seeking to hire a postdoctoral appointee to conduct research and modeling-based
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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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communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Preferred skills and qualifications: Experience with MPI and other communication libraries
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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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, 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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of chemical synthesis and characterization techniques Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker
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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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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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years. It has developed the GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model for estimating energy use, air emissions, and water consumption on a life-cycle basis for
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journal papers and patents. Ability to present research at technical meetings and publish results in peer reviewed journal articles. Ability to model Argonne’s core values of impact, safety, respect