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evaluate feature engineering and data representation strategies for heterogeneous datasets obtained from material synthesis, characterization, and functional testing. Apply uncertainty-aware modeling, active
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on experimental analysis, theoretical understanding and predictive modelling of complex mechanical behavior in engineering materials at different length scales (e.g, plasticity, damage, fracture), which emerges
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Start Date: Between 1 August 2026 and 1 July 2027 This project aims to frame hypersonic aerodynamics as a grand inverse problem. By combining modern state-of-the-art AI (foundation models, physics
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of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping the technologies that underpin a more sustainable and
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Building engineer or Environmental Science, Planning, Engineering, computer science, innovation science or related fields with demonstrable experience in spatial analysis and numerical modelling
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marine technology, together with more than 60 PhD students from all over the world. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning
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1st March 2026 Languages English Norsk Bokmål English English Would you like to explore how technology can transform the way we create and experience audiovisual stories? We now have two vacant
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real-time rerouting recommendations. Beyond the PhD, the project’s data-driven models will evolve through continuous real-world updates, contributing to sustainable aviation practices and climate-aware
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loading conditions. By generating datasets from finite element simulations, ML models can learn the mapping between unit cell design parameters and homogenised properties. State-of-the-art approaches
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between wind farms and MS motivating our central research questions: “do turbine driven changes in the MBL promote or hinder MS formation?” and “how does this modified rate of MS formation affect the