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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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skills in quantitative modelling and analysis Strong written and verbal communication skills in English The following experiences will strengthen your application: Master thesis involving life cycle
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Computational Arts, Music, and Games within the DSAI division. About the research project This position is related to investigating learned cultural representations in data search spaces of generative AI models
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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Master’s degree in Applied Mechanics, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding
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materials for synthesizing different types of hydrogen storage molecules. Using advanced quantum mechanical calculations, you will develop multi-scale models to study reaction kinetics and improve catalyst
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Materials Science are found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production - and in the interaction between these areas
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introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop
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developing AI methods for automated microstructure analysis and 3D microstructure generation. By combining self-supervised learning and diffusion-based generative models, the goal is to: Reconstruct high
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for Sustainable Housing and buildings”, you will: Develop an ontology of regenerative building production by analyzing how regeneration affects on-site praxis, economic structures, and business models and