83 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral research jobs at Argonne
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technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will assist with data collection, analysis, and scenario modeling for a DOE-sponsored assessment
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the ability and motivation to develop expertise in large-scale model training and scaling on HPC systems, as well as in handling the unique characteristics of scientific data, including large-scale numerical
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Leadership Computing Facility (ALCF), the Mathematics and Computer Science Division (MCS), the Computational Science Division (CPS), and the Data Science and Learning Division (DSL). The postdoctoral
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optical and THz techniques. Ability to analyze and understand complex data set is required. Experience to lead ultrafast x-ray scattering or electron scattering experiments is a plus but not required
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data analysis, documentation, and scientific communication skills, including preparation of manuscripts, reports, and presentations. Ability to model Argonne’s Core Values: Impact, Safety, Respect
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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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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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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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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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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