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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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Fellowship period at 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
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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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. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Job description The person hired in the position will work on theoretical control and optimization
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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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, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a
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one of the following areas is required: Numerical methods for large-scale, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and
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the advances in battery technology, as it enables more precise monitoring, control, and optimization of battery performance throughout its lifecycle. By incorporating digital tools such as algorithms, and
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are expected to be the CO2 capture technology for early large-scale deployment. A detailed understanding of the CO2 capture solvent is therefore necessary to ensure development and application of an optimal