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and optimization techniques, this research aims to identify optimum design and operational strategies that enhance system flexibility, improve resilience to variable supply and demand, and minimize
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the University of Oslo. Job description The person hired in the position will work on theoretical control and optimization methods for a grid island powered by renewable energy, supporting both
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monitoring of compound uptake into P. aeruginosa to guide the optimization process. The project is part of an interdisciplinary collaboration between research groups across several European countries and
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covalent and non-covalent inhibitors and will implement early monitoring of compound uptake into P. aeruginosa to guide the optimization process. The project is part of an interdisciplinary collaboration
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deployment. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This limits the ability to optimize energy storage use for critical
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, detecting pesticides and pathogens in agricultural production. In this part of the research, the goal is to optimize local CNT growth conditions at low temperature using different catalyst materials, while
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optimization methods for a grid island powered by renewable energy, supporting both the ATLAST telescope and the nearby community of San Pedro de Atacama. The PhD candidate will have the unique opportunity
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. Material Optimization: Use optimization algorithms to design FGMs that meet demanding performance criteria like fatigue resistance and durability. Systems Integration: Apply a systems engineering approach to
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to create new designs that optimize water yield. The project aspires to elucidate the physics governing droplet impact and wetting on fibrous networks in order to enhance fog net technology. The planned work
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fluid mechanics involved as droplets flow on and through fog nets, aiming to create new designs that optimize water yield. The project aspires to elucidate the physics governing droplet impact and wetting