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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
vulnerabilities. The Postdoctoral Appointee will be responsible for the conceptual framework, design, and implementation of these models, ensuring scalability on the DOE’s leadership computing facilities. Position
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Hands-on experience with two-dimensional materials modeling Proficiency in database development and management for computational materials data Strong programming skills and experience with software
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in high-impact venues Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of High Energy Physics or Nuclear Physics, or a closely related discipline
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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will require working on-site in Lemont, Illinois, 5 days a week Position Requirements Required skills, knowledge and experience: A recent or soon to be completed PhD within the last 0-5 years Molecular
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and is based at Argonne National Laboratory (Lemont, Illinois). Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in high energy physics, or a related field Experience
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leaching, solvent extraction, ion exchange, electrodialysis, membrane separation, and crystallization or precipitation. Position Requirements Recent or soon-to-be-completed PhD (typically completed within
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Laboratory’s Biosciences Division, allowing for seamless computational and experimental research integration Position Requirements A recent or soon to be completed PhD within the last 0-5 years Computational
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positions is to work on AI/ML with applications to cosmological modeling and surveys. Another open position is to work with Matthew R. Becker on weak gravitational lensing analysis with Rubin LSST data
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data