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energy supply chain strategies. Apply advanced analytics and methods to analyze trade, production, and geopolitical data to identify risk in critical supply chains. Develop and maintain analytical models
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increasing independence in defining research problems, developing methodologies, and driving publications. The role values strong research judgment and analytical thinking, complemented by effective use
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design, advanced modeling and high-performance computing, mathematics and data analytics, AI/ML algorithm development, and accelerator operations Ability to model Argonne’s core values of impact, safety
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-completed PhD (typically completed within the last 0-5 years) in chemical engineering, environmental engineering, or similar degree. Experience with data collection, processing, analysis, and presentation
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics—ideally in accelerator science or engineering—or a closely related field Demonstrated experience or strong interest
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, materials synthesis, and separation processes. Position Requirements Recent or soon-to-be-completed PhD (typically within the last 0–5 years) in chemistry, geochemistry, chemical engineering, physics
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diverse data sets, applying advanced analytics, and leveraging ML/AI techniques to detect, quantify, and forecast global risks affecting sourcing strategies. It will also include assessing AI-driven demand
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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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Position Requirements • Recent or soon-to-be-completed PhD (within the last 0-5 years) in the field of organic, organometallic, or inorganic chemistry, or a related field • Ability to model Argonne’s core
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partners to integrate findings into system-scale designs. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Chemical Engineering, Materials Science