44 data-"https:"-"https:"-"https:"-"https:"-"INSA-LYON" Postdoctoral positions at Argonne
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availability. Relevant Publications: 1. P. Chen et al., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1. 2
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below: https://www.anl.gov/cse/atomic-molecular-and-optical-physics Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in physics, chemistry, materials science, or
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solver, capable of running simulations on the Aurora supercomputer, using AMReX ( https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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position will contribute to the Forge project, which is focused on developing advanced multimodal AI capabilities that can learn across distributed data environments without requiring sensitive data to
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; assisting with data analysis and technical documentation; and contributing to publications, reports, and sponsor deliverables. The successful candidate will work closely with staff researchers and
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thin films and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning
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; perform experiments independently and collaboratively; and analyze, interpret, and report experimental data. Build and refine data-analysis, automation, and closed-loop decision-making workflows
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-based models for large dynamical systems (e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with
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. The successful candidate will develop a novel multiscale multimodal experimental apparatus with precise control during data acquisition, as well as work on data processing pipeline, adaptable to imaging