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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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chemistry and experience with quantum chemistry packages (e.g., Molpro, NWChem) Strong skills in developing and implementing computational and numerical methods; familiarity with parallel computing on CPU/GPU
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team and contribute to IDEAS (Intelligent Data Exploration Assistant for Science), a multi-year research effort focused on developing AI-powered visualization systems that enable interactive, human-in
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facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and
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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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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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computational materials science aligned with CNM strategic themes and the DOE mission Publish in refereed journals and present at conferences, symposia, and seminars Contribute to proposal development and assist
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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collaboration with team members. Skilled written and verbal communicator, including the ability to present complex information so that it is understandable to a broad audience. Computer skills relevant for data
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methods for designing safer and more reliable components. The researcher will also contribute to technical reports, conference papers, and journal publications, and present findings at technical conferences