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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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and interest in Design Patterns, algorithms and systems architecture. Interest in functional programming and other programming paradigms is also relevant. ETL, data wrangling and data analytics
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the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world
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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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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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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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the advances in battery technology, as it enables more precise monitoring, control, and optimization of battery performance throughout its lifecycle. By incorporating digital tools such as algorithms, and
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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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associated with the Center for Digital Narrative (CDN) , a Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural
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Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural contexts in which digital narratives are received and