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to understanding the phenomena. Identifying the fundamental variables, trade-offs and relationships that are most important to studying the phenomena and formalizing them in a measurement model. Developing and
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. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve using tools from mathematical machine learning
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environments. The project will build on an interdisciplinary approach, combining concepts and methods from physics, chemistry, and mathematical modelling. The long-term goal is to derive design principles
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manner. Join us! In industry, vast amounts of data are generated and stored. Often, this data is used in a straightforward manner; however, due to its sheer volume, existing methods struggle to convert it
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of positively and negatively charged polyelectrolytes will be the basis for a new method for the fabrication of membranes, requiring only water as a solvent. The porous structure of the membrane will be
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such scenarios, maps must be created or transformed from other maps. The ERC funded project GeoTrAnsQData project addresses this by developing a GeoQA method that converts questions into executable geo-analytical
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human perception and cognition. Experience in: experimental methods, computer rendering or VR/XR, programming. Affinity with multidisciplinary work, combining science, art, and technology. Enthusiasm
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a multidisciplinary problem centered around computational mechanics and engineering, potentially involving (i) multiphysics problems, (ii) multiscale methods, (iii) uncertainty quantification and (iv
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methods that enable designers to improve manual repair and automated remanufacturing using 3D-printing technologies. Job description We are looking for two PhD candidates who will contribute to the ADD-reAM
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning