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. Experience working in a geotechnical and chemical laboratory Experience working with georeferenced data Strong quantitative skills, including experience using numerical approaches. Experience working with
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strong theoretical and numerical foundation in FEM, with applications in adaptive and performance-driven design. The work supports the broader goal of transforming how engineers and architects
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the gap between numerical simulations and clinical practice. The candidate will work alongside experts in solid mechanics, finite element analysis, and machine learning and cardiology, benefiting from
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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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of the position System design and architecture of photonic integrated microwave system Design and modelling of electronic and photonic subsystems and numerical simulations Photonic chip design and tape-out in
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group conducts research on concrete from material to structural level based on theoretical, numerical and experimental investigations. The Concrete group is involved in several national and international
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short fiber thermoplastic composites Develop and validate numerical models and simulations to predict material and component performance Be prepared for changes to your work duties after employment
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-breakdown tests of cable peelings will be done at different stages of ageing to establish a foundation for improved physics- based ageing models. This will be incorporated into new numerical models
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address this challenge using advanced experimental techniques, numerical simulations, and machine learning methods to develop high-fidelity 3D renderings of deformed samples during physical tests. By
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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