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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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flexibility. To fully unlock this potential, we need advanced tools that digitally replicate these networks and support optimized design and data-driven control strategies. As our PhD candidate, you will
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large-language models (LLMs) are about to turn computer-aided engineering into true human–AI co-design. In the new MSCA Doctoral Network GenAIDE we team up with Honda Research Institute Europe, Altair
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gold standard of geo-analytic purposes and questions; collaborate with a technical assistant, another PhD candidate (on geodata source modelling), and a postdoc (on the GeoQA reasoning engine). It is
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? Generative AI and large-language models (LLMs) are about to turn computer-aided engineering into true human–AI co-design. In the new MSCA Doctoral Network GenAIDE we team up with Honda Research Institute
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Why apply? Generative AI and large-language models (LLMs) are about to turn computer-aided engineering into true human–AI co-design. In the new MSCA Doctoral Network GenAIDE we team up with Honda
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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sensing hardware into a high-throughput sorting line is a plus. Proficient in developing, training, and deploying AI-driven sensor-fusion pipelines, including preprocessing, deep-learning model
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areas include, amongst others, personalised and adaptive systems, user modelling and recommender systems, human interaction with embodied AI, and persuasive technology. You will work closely with other