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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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The Applied Materials Division (AMD) in the Emergent Materials and Process Group at Argonne National Laboratory in looking for a Post-doctoral Appointee -- Pyrometallurgy. The candidate will perform
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for a predoctoral/postdoctoral researcher position in research data management. Position Overview The candidate will manage and coordinate data activities across ESRA. You will work closely with
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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. This Postdoc will join the AL/ML group, a vibrant multidisciplinary team
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and technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will conduct comprehensive supply chain mapping, modeling, and analysis—integrating
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for molecular design (e.g., DFT, MD, AI/ML) is desired, but not required. · Strong oral and written communication skills are required. · Ph.D. in an experimental discipline, such as chemistry, materials
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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experimentalists, modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a related field
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer