87 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Keele-University" positions at Argonne
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training or analysis of scaling behavior. Familiarity with challenges such as data heterogeneity, communication efficiency, or system constraints. Exposure to privacy, robustness, or security techniques (e.g
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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design, advanced modeling and high-performance computing, mathematics and data analytics, AI/ML algorithm development, and accelerator operations Ability to model Argonne’s core values of impact, safety
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Type Full time The expected hiring range for this position is $72,879.00-$121,465.00. Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will
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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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data to guide intelligent data processing strategies and inform detector and readout device design Work collaboratively within a cross-disciplinary team and contribute to publications and presentations
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Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational
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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 Data Science and Learning Division (DSL) of the Computing, Environment and Life Sciences Directorate (CELS) and the Materials Science Division (MSD) of the Physical Sciences and Engineering
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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