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using Contactless Sensors Integrated with Operational Modal Analysis (TORSION)”. The main aim of this project is to develop a condition monitoring system with contactless sensors for critical components
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of associated ecosystems under events of wastewater discharge, industrial discharge, and urban runoff. In the Muncipality of Ålesund in Norway, a network of sensors has been installed in a drinking water source
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to enhance their indoor environment in a sustainable and cost-effective way. Simulations in combination with IoT sensors and devices, real-time data collected from pilot-scale and a residential building will
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criteria Competencies on IOT and Sensor technologies Competency and experience in AI methods Good communication skills - written and oral Good oral and written presentation skills in Norwegian/Scandinavian
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Background in probabilistic methods Experience with the application of AI algorithms and probabilistic methods Good programming skills Personal characteristics To complete a doctoral degree (PhD), it is
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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detection and classification algorithms using measured and/or simulated data, such as current pulses from cable faults (breakdown), partial discharges and external noise. In addition to being part of
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of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning