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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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within the last 5 years or upcoming year. A strong background in condensed matter physics and materials science. Excellent written and oral communication skills are needed. The ability to work
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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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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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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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tomography and/or X-ray techniques) to monitor fouling, scaling, and other degradation processes. Conduct experimental studies on fouling and scaling in pressure-driven membrane systems (UF, NF, RO) under
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automated experimental systems to measure electrode performance and durability over extended operation. Investigate electrode material performance, aging, and degradation mechanisms for bioprocessing
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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
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. Education: Ph.D. (< 5 yrs. since Ph.D.) • Familiarity with image processing and simulation software. • (Preferred) Experience with nanofabrication, transport measurements, thin film deposition, in-situ TEM