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researcher will be responsible for making measurements with advanced ultrafast optical spectroscopies, analyzing and interpreting complex spectroscopic data to map the full trajectory of excited-state
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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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data-intensive operations in scientific and AI applications. Investigate machine learning techniques to inform heuristic methods for routing optimization, bridging theoretical insights with practical
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at Materials Engineering Research Facility (MERF) and collaborators inside and outside Argonne. The candidate is expected to design and conduct experiments, analyze data and explore mechanisms behind
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, synthesize, and process information to develop high-quality datasets and derive empirically driven results; work with other team members to develop and apply cutting-edge methodologies to address critical
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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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A postdoctoral position on exascale atomistic simulations, AI/machine learning and data analysis of ferroelectric devices is available immediately at the Center for Nanoscale Materials (CNM
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Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is $70,758.00-$117,925.00. Please note that the pay range information is a general guideline only. The pay
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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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, and analyze scientific data specifically related to climate risks, including extreme weather events, long-term environmental changes, and their impact on infrastructure and ecosystems. This role