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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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data and data integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal
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data science approaches includes the application of Bayesian inference or probabilistic machine learning to geophysical models. UiO is subject to the Security Act, which governs the organisation's
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data science approaches includes the application of Bayesian inference or probabilistic machine learning to geophysical models. UiO is subject to the Security Act, which governs the organisation's
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objective is to develop methods that move beyond correlation-based prediction toward causal reasoning, intervention-aware modelling, and interpretable AI systems. This transition from correlation to causation
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research proposal (hf.uio.no ) stating how they intend to address the central research questions and offer theoretical and methodological approaches to attend to the project’s objectives. Preference will be
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(SEM), multi-level modelling, Bayesian statistics, or approaches combining quantitative data analyses with machine learning. Documented experience in teaching and related activities, such as
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systems, and multi-objective optimization. Prof. Freja Nygaard Rasmussen – life cycle assessment Prof. Sebastien Gros – decision-making, energy use, AI and machine learning Dr. Signe Riemer-Sørensen - AI