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the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes. The prospective postdoctoral appointee will perform multi-physics and multi-scale CFD simulations
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multi-physics simulation code for propulsion applications. The candidate will perform multi-scale computational fluid dynamics (CFD) simulations involving two-phase flows and combustion/reaction dynamics
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be to develop high fidelity simulations and/or algorithms to enable Bragg coherent diDraction imaging. We expect x-ray ptychography and coded aperture methods to play a fundamental role in creating a
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machine learning expertise, with the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes. Perform high-fidelity CFD simulations of complex physical
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The Nuclear Science and Engineering (NSE) Division is seeking a postdoctoral appointee to develop computational methods and computer codes to model the physics and engineering of advanced nuclear
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capability and scalability of multi-scale and multi-physics simulation codes. Develop turbulent combustion models for predictive CFD simulations of combustion dynamics in rotating detonation engines (RDEs
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of urbanization on precipitation, and aerosol-cloud interactions Strong modeling skills and high-performance computing experience Experience with model code development, and strong programming skills (e.g., Fortran
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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in soil processes, plant physiology, plant traits, and species composition Strong data analysis skills, including proficiency in R or Python coding, and/or machine learning techniques Excellent writing
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of modern collaborative coding practices Demonstrated experience with the application of multiphysics modeling to model complex physical phenomena Strong interpersonal, written, and oral communication skills