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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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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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data processing and interpretation workflows. The appointee will also pursue a collaborative science program leveraging the developing instrument capabilities, leading to peer-reviewed publications and
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will be working with ALCF’s technical teams (e.g., AI/ML, Data Science, Performance Engineering) and will focus on collaborative APEX research projects. We are looking to hire four Postdoctoral
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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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with this group to evaluate AERIS at S2S scales, couple ocean component to the model, data assimilation and regional refinement. In particular, this position will utilize generative AI to create a
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design, development of supervisory control logic, validation of vehicle models against test data etc. The projects and interests of this group span all modes of transportation including off-road, rail
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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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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