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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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-principles and atomistic simulations with machine-learned interatomic potentials to: Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps. Construct atomistic
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and simulation of the electronic structure of polycrystalline and defective two-dimensional materials. Interviews will begin immediately and continue until the position is filled. This position centers
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simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales. Key Responsibilities Design, implement, and validate physics-informed AI/ML
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extreme regional compound flooding within a global Earth system model. The aim is to enable realistic coastal flooding simulations within seasonal-to-decadal simulations and to advance DOE’s capability
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at the University of Chicago, automating screening protocols in partnership with Argonne National Laboratory Drive research at the intersection of automation, robotics, generative AI, and computational simulations
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attachments to your application via Workday : CV/Resume Unofficial Ph.D. Transcripts If already awarded, a copy of your Ph.D. diploma. Candidates can be currently enrolled to apply, but must have proof
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samples with significantly higher temporal resolution than traditional scanning methods. The selected candidate will simulate and design the experimental setup, and then perform single-frame ptychography
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emphasize multi-wavelength survey science, the galaxy-halo connection, cluster cosmology, and large-scale cosmological simulations. Analysis efforts cover topics such as CMB power spectra, CMB lensing, galaxy