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: 10.1038/s41467-023-39984-3 Position Requirements This level of knowledge is typically achieved through a formal education in Physics, or a related field at the PhD level with zero to five years
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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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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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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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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become part of a new holotomography software package actively being developed by the team. Position Requirements Required Knowledge, Skills, and Experience: PhD (recently completed or soon-to-be completed
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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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skills and qualifications: A recent PhD (completed within the last 5 years) in computer science, electrical engineering, or a related field. Strong background in network interconnect design and
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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