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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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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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to analytical techniques for characterizing effluent analytes using LC-MS, GC-MS, IC, ICP-MS, including developing in situ measurement routines aimed at understanding degradation mechanisms of membrane and
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The ALCF has an opening for a postdoctoral position in AI-assisted scientific visualization and intelligent data exploration. The successful candidate will join the Visualization and Data Analytics
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linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with
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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full
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in artificial intelligence and machine learning, particularly for control applications Proficiency in Python Strong analytical and problem-solving skills Ability to work independently and
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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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streams to products. An understanding of process scale-up and chemical plant design is of importance as well. The candidate should be familiar with databases and analytical models relevant to process
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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