87 data-"https:" "https:" "https:" "https:" "https:" "https:" "P" "LaTIM Brest" Postdoctoral research jobs at Argonne
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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-aware refinement strategies that go
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks an outstanding postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials
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, design of experiments, image and data processing. Position Requirements Recent or soon-to-be-completed PhD with strong background in Physics or Materials Science (within the last 5 years) Physics
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and technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will conduct comprehensive supply chain mapping, modeling, and analysis—integrating
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
to the ISAAC data repository by generating AI-ready physical descriptors and advancing data-driven understanding of dynamic catalytic processes. Responsibilities include : Identifying relevant user systems and
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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optical transition and favorable spin properties of individual solid-date erbium ions (Er3+) to store quantum information necessary for practical, robust, and scalable quantum communication. The focus
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user
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bioreactors; collect, analyze, and interpret biological, chemical, and microbial omics data; and integrate results to evaluate process performance and scalability. The candidate will contribute to process