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- University of Oslo
- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
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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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page to watch video, or click here to open video) About the position The position is part of the research project “Prediction of genetic values and adaptive potential in the wild (GPWILD)” (https
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3rd August 2026 Languages English English English We are looking for a PhD Candidate in Multi-scale, -physics, -fidelity wind modelling for wind farms Apply for this job See advertisement This is
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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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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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interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
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production, storage, consumption, and market interactions. This transition is fundamentally reshaping the structure of energy networks, shifting from centralized control to distributed, prosumer-driven
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position This PhD project is connected to FME NorthWind (https
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and limitations arising from the use of AI-based methods in predictive feedback. The successful candidate will: explore how a combination of multimodal observation (audio, video, LIDAR, thermal vision
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physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data