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future grid challenges, including widespread integration of DERs. The selected candidate will model, analyze, and control electric distribution and transmission systems, applying state-of-the-art
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and written Strong collaboration and teamwork abilities Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications: Experience in qubit control
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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deposition (ALD). The project involves performing quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms
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: Experience with generative models (transformers, diffusion models, VAEs, GANs) applied to biological sequences Familiarity with the theory behind modern molecular biology techniques Knowledge of HPC
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of chemical and electrochemical principles to control and improve product morphology, product quality, and process efficiency at engineering scales. With guidance, the appointee will : Develop novel process
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience: Background in economic theories and their application to overall or specific energy, mining, and manufacturing sectors
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Knowledge, Skills, and Experience: Proficiency in mathematical analysis and operator theory. Experience working with microelectronics. Experience in conducting synchrotron experiments and analyzing
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effects on fluid behavior in reacting and non-reacting flow applications. Understanding of combustion theory and modeling applied to combustion engines and other propulsion systems. Understanding of Finite