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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to build a physics
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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campus in Lemont, Illinois five days per week. Preferred Qualifications Proficiency in programming (e.g., Python) for advanced data analysis, machine learning, and computer vision to accelerate insights
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++, or similar, with experience in data-driven workflows and computer vision Demonstrated track record of peer-reviewed publications Highly collaborative, innovative, and capable of working independently in a
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, Quantum Information and Quantum Simulation. The successful candidate will be expected to carry out an independent and collaborative research program in particle theory that strengthens and complements
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This is an opportunity for a knowledgeable and creative individual to be part of a team using artificial intelligence and high-performance computing to evaluate the state of health (SOH
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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Research and Development Authority (BARDA). Together, these partners are advancing pandemic preparedness through AI-driven pathogen forecasting. The postdoctoral researcher will validate computational
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multidisciplinary team, the candidate will work at the intersection of AI/ML, domain sciences, and high-performance computing. The role requires a strong foundation in LLMs and machine learning, along with