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development of simplified continuum-based models, enabling fast assessments across large quay wall networks. This position is part of the Bridge and Quay Walls (Bruggen en Kademuren) programme of
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-personalised services - as Large Language Models become widely accessible, they're reshaping how we live, work, play and connect. This rapid shift sparks big questions: Whose norms and values shape this AI
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value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions
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-informed ML Experience working with Linux and HPC environments is an advantage. Strong communication skills and excellent proficiency in English. You enjoy working in an international, interdisciplinary team
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, or materials informatics. Familiarity with explainable AI or counterfactual explanation methods. Experience with molecular dynamics data, graph neural networks, or multi-component system modelling. Track record
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; Demonstrated interest or experience in sustainability transitions, circular economy, waste management, or environmental governance; Good networking and communication skills and ability to work independently and
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more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why
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to ESA’s strategy; a wide network of relationships and collaboration with top academics, industry and research centres; the opportunity to contribute to the Φ-lab strategy and activities. As an internal
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environment with an open culture, where you can be yourself and we pay attention to each other and to the world around us. Make the most of our bicycle budget, or join networks such as Young@EUR Opens
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datasets. Within this project most communication will be in English, so fluency in English and excellent communication and organizational skills are essential. You are communicative, well organized