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Field
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adaptive systems that jointly optimize morphology and control for real-world physical interaction. Requirements Ph.D. in Computer Science or a related discipline. Strong background in Machine Learning
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. Role & Responsibilities: Design and optimize large-scale electrophysiological and behavioral experiments using next generation custom-built hardware and software platforms Develop and implement end
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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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sluice, which will then be used in a learning framework to design an automatic controller to optimize the usage of the sluice under various conditions. The other project will address challenges related
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closed-loop optimization. Benchmark AI-assisted methods against classical control approaches and assess scalability and robustness under realistic noise conditions. 2. Neural Ansätze for Quantum
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Associate on the track of Smart Integrative Energy Systems will participate in the research efforts of developing systems integration, analysis, design, control, and/or optimization models and algorithms
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-products. Monitor and control the migration of radionuclides and heavy metals throughout industrial processes. Optimization of Industrial Processes: Utilize nuclear techniques to enhance the efficiency and
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performance testing (e.g., polarization curves, EIS). Design and execute experiments for materials optimization and degradation analysis. Maintain and operate laboratory equipment, including potentiostats
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reactors and the study of sonochemical reaction engineering. We excel at controlled experiments aimed at determining the driving forces for optimally efficient sonochemistry across different reactor scales
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advanced process control strategies and deploy them on the center's distributed control systems and edge computing devices. Work closely with industry partners to validate and optimize the developed