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of Stavanger (UoS). The position is funded within the project “SURF: “Subsurface Understanding for Robust emissions Forecasting”. SURF is funded by the Research Council of Norway and industry partners. We
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interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
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. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning models that forecast
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optimization of energy systems. A key goal of this project is to incorporate forecasting and market data (e.g., weather, electricity, fuel, and emission prices) to enhance optimized system operation