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at global scale. SUNRISE will challenge the state of the art by (i) producing new comprehensive data collections that can serve as references for future studies, (ii) enhancing the understanding of physical
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they learn, PRL134, 147402 (2025). Qualifications We seek candidates with: A PhD in physics, applied mathematics, materials science, mechanical engineering, computer science, or a related field. Strong
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of the queer intellectual in close collaboration with the research team (including the PI and the PhD); publishing in leading international peer-reviewed journals and contributing to a final edited
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scientific development of design tools and assessment frameworks that enable circularity in durable aerospace components. You will generate insights that directly inform the design process in other work
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; the advent of the Solar System internet and the associated challenges in network management and operations concepts, for example, new forms of user-machine interfaces, such as AR/VR; new ways to leverage
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, collaborate openly across institutions, and have the stamina to push through the engineering challenges that come with real-world physical AI. Your experience and profile: a PhD degree in Computer Vision
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multimodal modeling, interaction design, and adaptive systems. Job requirements We are looking for applicants who have or expect to receive a PhD degree before joining the project. Applications have a relevant
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transition, we encourage you to apply. Job requirements PhD degree in Chemistry, Materials Science, Physics, or a closely related field (completed by the time of appointment). Demonstrated expertise in
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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collaboration with a PhD student at the faculty of Industrial Design Engineering of TU Delft. You will be working on the sensing system in the armband. This will include the sensing yarn, a microfluidics system