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of complex propulsion systems involving modeling of multi-phase flows, turbulent combustion, heat transfer, combustion, and thermo-mechanical fluid-structure interaction by further developing commercial/in
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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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The Advanced Grid Modeling group at Argonne National Laboratory's Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) is seeking a highly motivated Postdoctoral Researcher
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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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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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, written, and oral communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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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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external recognition in relevant areas. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires an on-site presence at the Argonne campus in Lemont
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physics phenomenology. Members in the Particle Theory Group work on physics within and beyond the Standard Model, phenomenology at current and future colliders, as well as emerging areas in Artificial
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at the APS, integrating x-ray optics and wave propagation models with realistic sample simulations based on dislocation dynamics and molecular dynamics of relevant materials. Significant attention needs