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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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behaviors of MEMS structures. Hands-on experience working with signal processing and RF testing instruments. Strong communication skills for working in a multidisciplinary team environment. Ability
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robust 3D imaging technique suitable across diverse scientific communities. This project has two interconnected aims. The first is to create an accurate “digital twin” of the experiment through end-to-end
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engineering team to translate the models into production. The successful candidate will be part of a cross-lab, highly inter-disciplinary team of experts in ML, applied math, HPC, signal processing
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-state representations for real-time analysis; investigate aggregator-driven DER coordination strategies for day-ahead scheduling and real-time operations under various market or reliability signals
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automation, high-throughput data acquisition, and real-time data processing, offering a unique opportunity to advance S/TEM capabilities, publish impactful research, and collaborate with a diverse group of
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and processing strategies aimed at achieving high performance, cost-effectiveness, and manufacturability. The selected candidate will leverage the capabilities of the Materials Engineering Research
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The Chemical and Fuel Cycle Technologies division at Argonne is seeking a Postdoctoral Appointee to join a multidisciplinary team developing molten salt-based chemical and electrochemical processes
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Lemont, Illinois. Preferred Qualifications: Solid knowledge and independent research capability in stochastic process, machine learning and data analytics with track records of publications. Job Family
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and