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- University of Oslo
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- NTNU - Norwegian University of Science and Technology
- University of South-Eastern Norway
- Western Norway University of Applied Sciences
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data
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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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to shape the renewable energy management system by developing novel real-time control & optimization algorithms. Pilot demonstrations on partner radio telescope facilities such as APEX and the Sardinia Radio
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why this PhD topic fits their interest/background. This statement of research interest should not exceed one page Desired qualifications: Good knowledge in programming language theory, algorithms
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archaeology, and material culture from a long-term perspective. The Department of Natural History conducts research in systematics and taxonomy, evolutionary genomics, phylogeography, population genetics, and
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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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, physiology, cell biology, genetics, aquatic biology, toxicology, ecology, and evolutionary biology. The Department also operates Finse research station, the Biological research station in Drøbak and UiO's
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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