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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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, Safety, Health, and Quality Assurance standards and policies Process and interpret experimental data; prepare manuscripts for peer-reviewed publications Present research findings at scientific conferences
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for developing new computational tools and AI/ML approaches to analyze and correlate data from multiple imaging modalities, including synchrotron tomography, x-ray fluorescence microscopy, visible light microscopy
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deployment, monitoring, and optimization of complex scientific data streaming workflows for current and future production infrastructures. The project will involve close collaboration with a team of systems
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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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equipped with world-leading full-field imaging instruments, including ultrahigh-speed imaging. The group also develops end-to-end scientific software, data analysis, and interpretation methods
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of impact, safety, respect, integrity, and teamwork. This level of knowledge is typically achieved through a formal education in materials science, physics or related discipline at the PhD level or
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The Scientific Software Engineering & Data Management Group in the X-Ray Science Division (XSD) at the Advanced Photon Source (APS) (https://www.aps.anl.gov/) invites applicants for a postdoctoral
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from 20 to 200 nm and temporal resolutions of less than 1 minute for 3D data acquisition. The PXM’s capability to operate at high X-ray energies (>20 keV) allows for enhanced penetration and reduced
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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