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on designing and synthesizing advanced materials for next-generation batteries—such as solid-state, multivalent-ion, or aqueous rechargeable systems—while collaborating with the research team to optimize
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generalized, cross-layer defense framework that integrates network-level mitigation and application-level optimization to comprehensively protect distributed AI training from network threats while maintaining
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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into two main areas: (1) material development and characterization to ensure optimal sensing and mechanical performance, and (2) structural evaluation of SS-FRCMs under environmental stressors such as freeze
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urban catchments. Develop road designs that optimize water accumulation or flow. Create a framework for the selection and design of climate-adapted roads. The research will primarily involve hydrological
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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the applicant: - For the dissertation and the subject relevant knowledge and skills, for example demonstrated strong background knowledge at advanced level especially related to automatic control, optimization
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor
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systems, complex networks, data-driven modeling, machine learning, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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extensive expertise in technology and systems for sustainable production of food and bioenergy, including optimal nutrition circuits and logistics systems. Within the field of methodologies, we have extensive