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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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of structures, facilitating a form-finding process driven by FEM analysis. Training deep learning algorithms to suggest multiple structural concepts tailored to specific boundary conditions. Expanding FEM
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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
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techniques for effective analysis of massive-size geophysical data. The goal is to develop algorithms for classification and predictions that enable early warning systems in various geosciences applications
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Sustainable Energy AS. Duties of the position The technical work tasks concern: Development of smart algorithms and modules for load prediction and minimization of fuel, energy, and emissions for marine vessels
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. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and navigation data sets as a part of