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to support increasingly complex cybersecurity exercises. RO3: Investigate simulation and predictive modelling approaches for analysing cascading cyber threats and evaluating the resilience of interconnected
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16th August 2026 Languages English English English The Department of Civil and Environmental Engineering has a vacancy for a PhD in Predictive AI-Based Maintenance and Optimization of Building
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products. At NTNU, a central part of the project is the development of more predictable and efficient methods for the refactoring and heterologous expression of biosynthetic gene clusters (BGCs). The PhD
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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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of flying birds to predict collision risk. This model will be fed by existing empirical data on bird flight behavioural responses to wind turbines from various bird radar studies. This model will allow
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products. At NTNU, a central part of the project is the development of more predictable and efficient methods for the refactoring and heterologous expression of biosynthetic gene clusters (BGCs
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an aerodynamic bird collision avoidance model, combining computational fluid dynamics (CFD) of the flow around wind turbines with the aerodynamic characteristics of flying birds to predict collision risk. This
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refinement. Accurate wind simulation at multiple scales helps in better predicting energy production and reducing operational risks. Some relevant key words (see FME-NorthWind webpage for more details
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on psychological development, mental health, and psychosocial functioning, the project will identify developmental trajectories of attachment and examine factors that may predict these trajectories. The overarching
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nested grids and adaptive mesh refinement. Accurate wind simulation at multiple scales helps in better predicting energy production and reducing operational risks. Some relevant key words (see FME