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Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine learning in general. OCBE has numerous collaborations with
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analysis. Experience with the use of High Performance Computing facilities. Insight into a range of machine learning methods and ideas. You need to: Write an application where you clearly demonstrate
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visions is to use artificial spin systems as a platform for efficient and powerful data analysis at all scales, ranging from low-power computation in the simplest sensor node to accelerated data processing
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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 environment are key priorities. As offshore operations grow more complex, the safe transfer of personnel and equipment to offshore structures for maintenance, repair, and monitoring has become increasingly
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. Severe leakage can lead to death in the worst cases. This condition involves complex remodeling mechanisms, resulting in poor prognosis. Major clinical challenges include predicting disease progression and
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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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an explicit aspect of security of electricity supply; tools to increase situational awareness. Methods for risk analysis of the complex interdependencies arising in the intelligent electricity
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, Resilient and Integrated Energy Systems, which is connected to NTNU Energy . NTNU Energy is aiming to address complex challenges through interdisciplinary collaboration activities. The PhD position will focus