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). The position is part of the research project ThermRisk: A Personalized Digital Human Model for Predictive Thermal Risk Assessment. ThermRisk is a collaborative project between three faculties at HVL: the Faculty
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solutions for offshore wind turbines, enabling to enhance their structural awareness, real-time reliability assessment, and predictive maintenance decision support through integrated sensing, modelling, and
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used to support real-time monitoring, predictive maintenance, geohazard detection, and safer railway operations. The initiative is a collaboration between the Department of Electrical Engineering, the
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energy imbalance (EEI) and ocean heat content (OHC), in order to close an existing knowledge gap and im-prove near-term predictions. Other partners in the project are University of Ber-gen and Nansen
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page to watch video, or click here to open video) About the position The position is part of the research project “Prediction of genetic values and adaptive potential in the wild (GPWILD)” (https
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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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ecosystems where interconnected multi-agents interact strategically in dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently
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well as resource limitations. 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
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the Department of Geosciences. PHAB’s main goal, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three
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and limitations arising from the use of AI-based methods in predictive feedback. The successful candidate will: explore how a combination of multimodal observation (audio, video, LIDAR, thermal vision