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Field
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brings together expertise in energy informatics, optimization, data science, social sciences, and governance to develop trusted data-sharing solutions for the heat transition. Within the project, you will
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methodologies for evaluating suitable storage sites and optimized lined rock cavern designs; - publish research findings in leading international scientific journals; - present research at national and
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develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration
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-to-confidence set conversion' framework recently proposed by the PI (Principal Investigator). The models of interest include deep neural networks with multiple layers and non-linear activations, extending recent
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modelling, laboratory testing and field investigations; - participate in site investigations and data collection in northern Sweden; - develop methodologies for evaluating suitable storage sites and optimized
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and prior knowledge of the sample geometry. You investigate and optimize the trade-off between accuracy and imaging speed. For real-time application, the speed and accuracy of the algorithms will be
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operate. The complexity and size of indoor optical systems pose challenges in scalability, power consumption, and maintenance. While wireless networks present a viable solution for indoor environments by
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systems, optimizing audio playback levels, and supporting other acoustic interventions to improve occupant comfort and building performance. The research will adopt a human-centered approach, placing
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Skłodowska-Curie Doctoral Network TRILOGY, an international training programme in ultrafast science, attosecond physics, and photonics. TRILOGY trains 14 doctoral candidates across leading European
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. The state-of-the-art approaches in optimal climate control of greenhouses are based on implementing economic objective functions exploiting a time scale decomposition between short-term climate control/energy