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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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- 1st September 2025 Languages English Norsk Bokmål English English Do you want to research work scheduling using artificial intelligence? PhD Fellowship in AI-Based Shift Scheduling: Optimization
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thermal imaging data, and potential clinical and signal data, to create algorithms capable of recognizing key clinical activities and interventions. Building on recent advances in computer vision and
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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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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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storage in depleted petroleum fields: In this project, you will investigate and aim to optimize CO2-assisted oil production (CO2EOR) and subsequent CO2 storage. Simplistic models for a fundamental
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integrated system, CNTs serve as the sensing elements, while necessary signal processing can be performed directly on-chip by the CMOS circuitry. The ultra-sensitive CNT-based sensors can be utilized in
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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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% position as PhD Research Fellow in “Pioneering AI and Sustainable Materials for Next-Generation Offshore Wind Turbines” from November 1st 2025, or by agreement. The position is at the Department of Process