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assessment of soil properties. Using 3D data and building information modelling (BIM), we will optimize excavation planning. The project requires interdisciplinary collaboration and advanced technological
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low alloy steels. To ensure their effectiveness, the project investigates how these barriers interact with hydrogen—studying uptake, diffusion, and mechanical performance—while also optimizing cladding
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mathematical modeling, numerical optimization and control. Knowledge in machine learning and data driven decision making methods. You must have a master's degree in engineering Cybernetics, Control Engineering
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Process Engineering at NTNU in Trondheim, Norway, and it is funded by the Research Council of Norway and the Norwegian hydropower industry. The research is both experimental and numerical and it is mainly
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methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered
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to accelerate the design and optimization of materials that can enhance performance, efficiency, and sustainability across various technologies. The successful candidate will conduct innovative research aimed
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the numerous timber bridges existing nowadays, research on fatigue in timber connections is extremely limited. Currently, the basis for the evaluation of fatigue of dowel-connections in typical timber truss
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optimal configurations, dimensions, and mooring systems through the development of efficient analysis tools and application of numerical optimization techniques. Are you motivated to take a step towards a