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are applied in real-world settings characterized by large-scale networks, stochastic demand, operational disruptions, and complex constraints. A central research question is how machine learning can be
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global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging
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analyses or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of
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team includes: Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning Prof. Mohamed Hamdy – building performance simulation, building automation
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-NorthWind webpage for more details): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer
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): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer the opportunity to work in a very
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system for ferry quays, containing labelled damage data as training material for a machine learning model capable of automatically classifying structural damage from drone inspection images. The project
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» Maritime engineering Engineering » Computer engineering Computer science Architecture » Naval architecture Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 23 Aug
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. The research team consisting of eight faculty members, the Industrial Ecology Digital Laboratory, and about 70 researchers, post doctors and PhD students. More information can be found at https
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at https://www.ntnu.edu/indecol . Your immediate leader is Dr. Martin Dorber. Prof. Francesca Verones, Assoc. Prof. Johan Berg Pettersen and Assoc. Prof. Tora Bonnevie are co-supervisors of the candidate